==================================================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_005/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_chunk.py . [hook] pytest_runtest_teardown:test_chunk_high_dimension[pynative] tests/st/mint/test_chunk.py::test_chunk_high_dimension[pynative],max_mem:2.0M TotalTime = 4.96986, [33] [bootstrap]: 0.00071876 [type_inference]: 0.944855 [event_method]: 1.767e-05 [auto_monad]: 0.00019218 [graph_reusing]: 6.48e-06 [pre_auto_parallel]: 1.22e-05 [py_interpret_to_execute]: 0.00012835 [rewriter_before_opt_a]: 8.198e-05 [expand_dump_flag]: 3.83001e-06 [jit_opt_a]: 0.0106575, [2] [Cycle 1]: 0.00258574, [27] [switch_simplify]: 6.795e-05 [loop_unroll]: 2.218e-05 [a_1]: 0.00049843 [with_stream_mark]: 3.138e-05 [recompute_prepare]: 1.167e-05 [updatestate_depend_eliminate]: 8.79e-06 [updatestate_assign_eliminate]: 1.023e-05 [updatestate_loads_eliminate]: 5.34e-06 [parameter_eliminate]: 2.01e-06 [specialize_transform]: 1.02e-05 [updatestate_useless_node_eliminater]: 1.155e-05 [accelerated_algorithm]: 8.64e-06 [meta_shard_fg_expand]: 3.25e-06 [get_grad_eliminate_]: 8.85001e-06 [merge_forward]: 6.28e-06 [cell_reuse_recompute_pass]: 1.30999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.328e-05 [j_node_and_user_rematch]: 1.507e-05 [meta_fg_expand]: 3.62998e-06 [replace_old_param]: 1.453e-05 [inline_without_move]: 8.65001e-06 [renormalize]: 0.0014164 [add_forward_monad_depend]: 9.17999e-06 [auto_monad_grad]: 2.78e-06 [auto_monad_eliminator]: 2.79e-05 [cse]: 7.3e-05 [replace_applicator]: 2.563e-05 [Cycle 2]: 0.00054042, [27] [switch_simplify]: 1.012e-05 [loop_unroll]: 8.30999e-06 [a_1]: 0.00017704 [with_stream_mark]: 1.755e-05 [recompute_prepare]: 8.36002e-06 [updatestate_depend_eliminate]: 6.56999e-06 [updatestate_assign_eliminate]: 1.051e-05 [updatestate_loads_eliminate]: 5.57001e-06 [parameter_eliminate]: 2.57001e-06 [specialize_transform]: 8.99e-06 [updatestate_useless_node_eliminater]: 1.086e-05 [accelerated_algorithm]: 8.89998e-06 [meta_shard_fg_expand]: 2.56998e-06 [get_grad_eliminate_]: 8.3e-06 [merge_forward]: 6.68e-06 [cell_reuse_recompute_pass]: 2.74001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.94e-05 [j_node_and_user_rematch]: 1.292e-05 [meta_fg_expand]: 3.38e-06 [replace_old_param]: 1.248e-05 [inline_without_move]: 7.87998e-06 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 1.55001e-06 [auto_monad_grad]: 1.40001e-06 [auto_monad_eliminator]: 1.504e-05 [cse]: 2.548e-05 [replace_applicator]: 8.89e-06 [py_interpret_to_execute_after_opt_a]: 1.932e-05 [rewriter_after_opt_a]: 0.00031612 [convert_after_rewriter]: 1.662e-05 [order_py_execute_after_rewriter]: 8.38001e-06 [mutable_eliminate]: 0.00080096 [jit_opt_b]: 7.601e-05, [1] [Cycle 1]: 6.551e-05, [2] [frontend_op_eliminate]: 2.532e-05 [inline_after_opt_a]: 2.661e-05 [cconv]: 4.054e-05 [loop_unroll]: 0.00049223 [jit_opt_after_cconv]: 0.156531, [1] [Cycle 1]: 0.156517, [11] [c_1]: 5.232e-05 [parameter_eliminate]: 5.68002e-06 [updatestate_depend_eliminate]: 1.385e-05 [updatestate_assign_eliminate]: 5.12999e-06 [updatestate_loads_eliminate]: 5.36002e-06 [cse]: 0.156147 [call_graph_tuple_transform]: 8.236e-05 [tuple_list_get_item_eliminator]: 1.37e-05 [none_parameter_eliminate]: 8.48999e-06 [renormalize]: 1.14998e-06 [switch_simplify]: 1.152e-05 [remove_dup_value]: 7.701e-05 [partial_unused_args_eliminate]: 3.27002e-06 [environ_conv]: 4.129e-05 [add_recomputation]: 0.0001102 [cse_after_recomputation]: 5.969e-05, [1] [Cycle 1]: 4.54e-05, [1] [cse]: 3.304e-05 [auto_monad_reorder]: 4.385e-05 [get_jit_bprop_graph]: 2.71e-06 [rewriter_after_jit_bprop_graph]: 0.00021595 [opt_after_jit_grad]: 0.00112027 [symbol_engine_optimizer]: 0.0001381, [1] [Cycle 1]: 0.000125, [6] [build]: 2.365e-05 [elim_shapecalc]: 1.436e-05 [elim_not_effective]: 2.665e-05 [opt_reshape]: 9.79e-06 [fold_const_symbol]: 1.38e-05 [renormalize]: 9.29984e-07 [validate]: 0.00010391 [backend_pass]: 1.51998e-06 [task_emit]: 3.8525 [execute]: 1.127e-05 Sums bootstrap : 0.000719s : 0.01% type_inference : 0.944855s : 19.04% event_method : 0.000018s : 0.00% auto_monad : 0.000192s : 0.00% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000128s : 0.00% rewriter_before_opt_a : 0.000082s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000078s : 0.00% jit_opt_a.loop_unroll : 0.000030s : 0.00% jit_opt_a.a_1 : 0.000675s : 0.01% jit_opt_a.with_stream_mark : 0.000049s : 0.00% jit_opt_a.recompute_prepare : 0.000020s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000021s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000011s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000019s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000022s : 0.00% jit_opt_a.accelerated_algorithm : 0.000018s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000017s : 0.00% jit_opt_a.merge_forward : 0.000013s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000043s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000028s : 0.00% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000027s : 0.00% jit_opt_a.inline_without_move : 0.000017s : 0.00% jit_opt_a.renormalize : 0.001416s : 0.03% jit_opt_a.add_forward_monad_depend : 0.000011s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000043s : 0.00% jit_opt_a.cse : 0.000098s : 0.00% jit_opt_a.replace_applicator : 0.000035s : 0.00% py_interpret_to_execute_after_opt_a : 0.000019s : 0.00% rewriter_after_opt_a : 0.000316s : 0.01% convert_after_rewriter : 0.000017s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000801s : 0.02% jit_opt_b.frontend_op_eliminate : 0.000025s : 0.00% jit_opt_b.inline_after_opt_a : 0.000027s : 0.00% cconv : 0.000041s : 0.00% loop_unroll : 0.000492s : 0.01% jit_opt_after_cconv.c_1 : 0.000052s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.156147s : 3.15% jit_opt_after_cconv.call_graph_tuple_transform : 0.000082s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000014s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000012s : 0.00% remove_dup_value : 0.000077s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000041s : 0.00% add_recomputation : 0.000110s : 0.00% cse_after_recomputation.cse : 0.000033s : 0.00% auto_monad_reorder : 0.000044s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000216s : 0.00% opt_after_jit_grad : 0.001120s : 0.02% symbol_engine_optimizer.build : 0.000024s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000014s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000027s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000104s : 0.00% backend_pass : 0.000002s : 0.00% task_emit : 3.852505s : 77.65% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.000274 43 3.76% : 0.000010s : 2: substitution.depend_value_elim 1.29% : 0.000004s : 4: substitution.elim_not_effective 0.73% : 0.000002s : 4: substitution.fold_const_symbol 4.07% : 0.000011s : 5: substitution.graph_param_transform 73.55% : 0.000201s : 2: substitution.inline 2.02% : 0.000006s : 8: substitution.j_node_and_user_rematch 2.84% : 0.000008s : 8: substitution.remove_not_recompute_node 2.64% : 0.000007s : 2: substitution.replace_old_param 4.92% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 4.18% : 0.000011s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.944751 2 99.84% : 0.943263s : 1: type_inference.infer 0.16% : 0.001488s : 1: type_inference.specialize ------[replace.] 0.000034 2 100.00% : 0.000034s : 2: replace.inline ------[match.] 0.000200 2 100.00% : 0.000200s : 2: match.inline ------[predicate.] 0.000158 767 1.33% : 0.000002s : 11: predicate.accumulaten_eliminater 3.13% : 0.000005s : 5: predicate.ad_related_special_op_eliminate 1.07% : 0.000002s : 11: predicate.addn_check_dump 1.11% : 0.000002s : 11: predicate.addn_zero_filter 1.90% : 0.000003s : 11: predicate.arithmetic_simplify 1.12% : 0.000002s : 11: predicate.cast_eliminate 0.53% : 0.000001s : 5: predicate.check_bprop_eliminate 1.04% : 0.000002s : 11: predicate.compare_switch_simplify 1.20% : 0.000002s : 11: predicate.depend_value_elim 0.99% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.22% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.06% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.86% : 0.000003s : 5: predicate.dumpgradient_eliminate 0.72% : 0.000001s : 5: predicate.elim_not_effective 0.92% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.03% : 0.000002s : 11: predicate.environ_add_const_eliminate 0.90% : 0.000001s : 11: predicate.environ_get_add_eliminate 0.91% : 0.000001s : 11: predicate.environ_get_depend_swap 0.98% : 0.000002s : 11: predicate.environ_get_eliminate 0.91% : 0.000001s : 11: predicate.environ_get_set_eliminate 0.29% : 0.000000s : 5: predicate.fold_const_symbol 1.66% : 0.000003s : 10: predicate.get_grad_eliminate 0.95% : 0.000002s : 5: predicate.graph_param_transform 5.12% : 0.000008s : 23: predicate.inline 1.16% : 0.000002s : 10: predicate.inline_without_move 0.51% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.75% : 0.000003s : 10: predicate.less_batch_normalization 1.14% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.75% : 0.000003s : 16: predicate.load_eliminater 2.07% : 0.000003s : 5: predicate.loop_unroll_after_grad 2.84% : 0.000004s : 20: predicate.loop_unroll_before_grad 2.12% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 0.91% : 0.000001s : 11: predicate.merge_addn 0.92% : 0.000001s : 11: predicate.minmaximum_grad 2.51% : 0.000004s : 5: predicate.mutable_eliminate 0.68% : 0.000001s : 5: predicate.opt_reshape 1.83% : 0.000003s : 16: predicate.partial_eliminate 1.11% : 0.000002s : 11: predicate.print_const_string_wrapper 1.58% : 0.000003s : 11: predicate.reduce_eliminate 1.30% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.75% : 0.000001s : 10: predicate.remove_not_recompute_node 1.60% : 0.000003s : 21: predicate.replace_applicator 0.80% : 0.000001s : 10: predicate.replace_old_param 0.56% : 0.000001s : 5: predicate.reset_defer_inline 1.42% : 0.000002s : 11: predicate.reshape_eliminate 1.31% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.79% : 0.000001s : 5: predicate.row_tensor_eliminate 1.41% : 0.000002s : 11: predicate.same_eliminate 0.61% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.36% : 0.000002s : 10: predicate.special_op_eliminate 1.15% : 0.000002s : 10: predicate.specialize_transform 1.36% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.12% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.54% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.63% : 0.000003s : 13: predicate.switch_defer_inline 1.29% : 0.000002s : 13: predicate.switch_layer_defer_inline 6.16% : 0.000010s : 38: predicate.switch_simplify 1.63% : 0.000003s : 11: predicate.tile_eliminate 1.07% : 0.000002s : 11: predicate.transpose_eliminate 1.48% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.41% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 4.62% : 0.000007s : 21: predicate.tuple_list_get_item_eliminator 1.38% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.13% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.49% : 0.000002s : 16: predicate.updatestate_pure_node_eliminater 2.90% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.41% : 0.000002s : 11: predicate.value_based_eliminate 0.56% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.94% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000609 6 34.66% : 0.000211s : 2: func_graph_cloner_run.FuncGraphClonerGraph 65.34% : 0.000398s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 4.972420 76 0.00% : 0.000115s : 1: add_recomputation 0.00% : 0.000198s : 1: auto_monad 0.00% : 0.000047s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: backend_pass 0.01% : 0.000744s : 1: bootstrap 0.00% : 0.000043s : 1: cconv 0.00% : 0.000021s : 1: convert_after_rewriter 0.00% : 0.000062s : 1: cse_after_recomputation 0.00% : 0.000046s : 1: environ_conv 0.00% : 0.000024s : 1: event_method 0.00% : 0.000018s : 1: execute 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 0.21% : 0.010661s : 1: jit_opt_a 3.15% : 0.156539s : 1: jit_opt_after_cconv 0.00% : 0.000080s : 1: jit_opt_b 0.01% : 0.000505s : 1: loop_unroll 0.02% : 0.000813s : 1: mutable_eliminate 0.02% : 0.000978s : 26: opt.transform.jit_opt_a 0.00% : 0.000145s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000044s : 4: opt.transform.jit_opt_b 0.00% : 0.000021s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000026s : 1: opt.transform.mutable_eliminate 0.00% : 0.000053s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000060s : 4: opt.transform.symbol_engine_opt 0.02% : 0.001145s : 1: opt_after_jit_grad 0.00% : 0.000011s : 1: order_py_execute_after_rewriter 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000015s : 1: pre_auto_parallel 0.00% : 0.000132s : 1: py_interpret_to_execute 0.00% : 0.000022s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000083s : 1: remove_dup_value 0.02% : 0.000933s : 1: renormalize.infer 0.01% : 0.000471s : 1: renormalize.specialize 0.00% : 0.000222s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000322s : 1: rewriter_after_opt_a 0.00% : 0.000087s : 1: rewriter_before_opt_a 0.00% : 0.000142s : 1: symbol_engine_optimizer 77.48% : 3.852540s : 1: task_emit 19.00% : 0.944880s : 1: type_inference 0.00% : 0.000142s : 1: validate TotalTime = 3.9887, [33] [bootstrap]: 0.00061681 [type_inference]: 0.878928 [event_method]: 0.0002226 [auto_monad]: 0.00031099 [graph_reusing]: 1.083e-05 [pre_auto_parallel]: 4.07e-06 [py_interpret_to_execute]: 6.171e-05 [rewriter_before_opt_a]: 0.00016681 [expand_dump_flag]: 4.08001e-06 [jit_opt_a]: 1.02115, [4] [Cycle 1]: 0.990531, [27] [switch_simplify]: 0.00031684 [loop_unroll]: 7.301e-05 [a_1]: 0.00223572 [with_stream_mark]: 4.817e-05 [recompute_prepare]: 3.967e-05 [updatestate_depend_eliminate]: 5.151e-05 [updatestate_assign_eliminate]: 1.267e-05 [updatestate_loads_eliminate]: 2.853e-05 [parameter_eliminate]: 4.92999e-06 [specialize_transform]: 2.555e-05 [updatestate_useless_node_eliminater]: 2.788e-05 [accelerated_algorithm]: 2.11e-05 [meta_shard_fg_expand]: 6.68e-06 [get_grad_eliminate_]: 1.976e-05 [merge_forward]: 1.325e-05 [cell_reuse_recompute_pass]: 2.07999e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.386e-05 [j_node_and_user_rematch]: 8.535e-05 [meta_fg_expand]: 0.425922 [replace_old_param]: 0.00018309 [inline_without_move]: 0.00017438 [renormalize]: 0.342387 [add_forward_monad_depend]: 3.297e-05 [auto_monad_grad]: 2.283e-05 [auto_monad_eliminator]: 0.00017202 [cse]: 0.00049946 [replace_applicator]: 0.217575 [Cycle 2]: 0.00976616, [27] [switch_simplify]: 0.00014355 [loop_unroll]: 0.0001301 [a_1]: 0.00543012 [with_stream_mark]: 5.376e-05 [recompute_prepare]: 4.143e-05 [updatestate_depend_eliminate]: 1.659e-05 [updatestate_assign_eliminate]: 1.785e-05 [updatestate_loads_eliminate]: 1.667e-05 [parameter_eliminate]: 6.54001e-06 [specialize_transform]: 2.673e-05 [updatestate_useless_node_eliminater]: 0.0001042 [accelerated_algorithm]: 4.176e-05 [meta_shard_fg_expand]: 7.9e-06 [get_grad_eliminate_]: 1.733e-05 [merge_forward]: 1.189e-05 [cell_reuse_recompute_pass]: 1.59e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.816e-05 [j_node_and_user_rematch]: 2.859e-05 [meta_fg_expand]: 0.00020013 [replace_old_param]: 2.976e-05 [inline_without_move]: 1.722e-05 [renormalize]: 0.00273042 [add_forward_monad_depend]: 1.295e-05 [auto_monad_grad]: 2.58e-06 [auto_monad_eliminator]: 4.6e-05 [cse]: 0.00023124 [replace_applicator]: 4.01e-05 [Cycle 3]: 0.0025094, [27] [switch_simplify]: 1.998e-05 [loop_unroll]: 1.609e-05 [a_1]: 0.00047662 [with_stream_mark]: 2.912e-05 [recompute_prepare]: 2.233e-05 [updatestate_depend_eliminate]: 6.593e-05 [updatestate_assign_eliminate]: 9.94001e-06 [updatestate_loads_eliminate]: 8.3e-06 [parameter_eliminate]: 2.58e-06 [specialize_transform]: 1.679e-05 [updatestate_useless_node_eliminater]: 1.942e-05 [accelerated_algorithm]: 1.974e-05 [meta_shard_fg_expand]: 3.97e-06 [get_grad_eliminate_]: 1.19e-05 [merge_forward]: 3.943e-05 [cell_reuse_recompute_pass]: 6.113e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.133e-05 [j_node_and_user_rematch]: 2.575e-05 [meta_fg_expand]: 6.48e-06 [replace_old_param]: 2.084e-05 [inline_without_move]: 1.324e-05 [renormalize]: 0.00118281 [add_forward_monad_depend]: 9.37999e-06 [auto_monad_grad]: 2.54999e-06 [auto_monad_eliminator]: 3.111e-05 [cse]: 8.271e-05 [replace_applicator]: 2.765e-05 [Cycle 4]: 0.00090064, [27] [switch_simplify]: 1.551e-05 [loop_unroll]: 1.301e-05 [a_1]: 0.00035855 [with_stream_mark]: 2.063e-05 [recompute_prepare]: 4.041e-05 [updatestate_depend_eliminate]: 1.202e-05 [updatestate_assign_eliminate]: 8.32e-06 [updatestate_loads_eliminate]: 6.96999e-06 [parameter_eliminate]: 3.23998e-06 [specialize_transform]: 1.631e-05 [updatestate_useless_node_eliminater]: 1.839e-05 [accelerated_algorithm]: 1.798e-05 [meta_shard_fg_expand]: 3.46001e-06 [get_grad_eliminate_]: 1.236e-05 [merge_forward]: 8.97e-06 [cell_reuse_recompute_pass]: 3.03e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.971e-05 [j_node_and_user_rematch]: 2.183e-05 [meta_fg_expand]: 4.92e-06 [replace_old_param]: 1.706e-05 [inline_without_move]: 1.293e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.58e-06 [auto_monad_grad]: 1.90001e-06 [auto_monad_eliminator]: 2.352e-05 [cse]: 5.164e-05 [replace_applicator]: 1.437e-05 [py_interpret_to_execute_after_opt_a]: 2.419e-05 [rewriter_after_opt_a]: 0.00037625 [convert_after_rewriter]: 1.984e-05 [order_py_execute_after_rewriter]: 9.62001e-06 [mutable_eliminate]: 0.00091812 [jit_opt_b]: 0.00034038, [2] [Cycle 1]: 0.00022454, [2] [frontend_op_eliminate]: 0.0001653 [inline_after_opt_a]: 3.616e-05 [Cycle 2]: 0.00010144, [2] [frontend_op_eliminate]: 5.516e-05 [inline_after_opt_a]: 2.966e-05 [cconv]: 4.236e-05 [loop_unroll]: 0.00059133 [jit_opt_after_cconv]: 0.00038195, [1] [Cycle 1]: 0.00037176, [11] [c_1]: 6.662e-05 [parameter_eliminate]: 6.65002e-06 [updatestate_depend_eliminate]: 1.697e-05 [updatestate_assign_eliminate]: 7.43e-06 [updatestate_loads_eliminate]: 6.39001e-06 [cse]: 0.00010161 [call_graph_tuple_transform]: 3.574e-05 [tuple_list_get_item_eliminator]: 1.199e-05 [none_parameter_eliminate]: 1.82999e-06 [renormalize]: 8.59989e-07 [switch_simplify]: 4.504e-05 [remove_dup_value]: 6.852e-05 [partial_unused_args_eliminate]: 3.70998e-06 [environ_conv]: 1.633e-05 [add_recomputation]: 0.00010054 [cse_after_recomputation]: 5.65e-05, [1] [Cycle 1]: 4.821e-05, [1] [cse]: 3.891e-05 [auto_monad_reorder]: 3.559e-05 [get_jit_bprop_graph]: 2.51998e-06 [rewriter_after_jit_bprop_graph]: 9.72999e-06 [opt_after_jit_grad]: 0.143413 [symbol_engine_optimizer]: 0.00015468, [1] [Cycle 1]: 0.00014234, [6] [build]: 2.377e-05 [elim_shapecalc]: 1.576e-05 [elim_not_effective]: 3.459e-05 [opt_reshape]: 1.285e-05 [fold_const_symbol]: 1.97e-05 [renormalize]: 1.13001e-06 [validate]: 7.704e-05 [backend_pass]: 1.30001e-06 [task_emit]: 1.94021 [execute]: 1.127e-05 Sums bootstrap : 0.000617s : 0.02% type_inference : 0.878928s : 22.14% event_method : 0.000223s : 0.01% auto_monad : 0.000311s : 0.01% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000062s : 0.00% rewriter_before_opt_a : 0.000167s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000496s : 0.01% jit_opt_a.loop_unroll : 0.000232s : 0.01% jit_opt_a.a_1 : 0.008501s : 0.21% jit_opt_a.with_stream_mark : 0.000152s : 0.00% jit_opt_a.recompute_prepare : 0.000144s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000146s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000049s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000060s : 0.00% jit_opt_a.parameter_eliminate : 0.000017s : 0.00% jit_opt_a.specialize_transform : 0.000085s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000170s : 0.00% jit_opt_a.accelerated_algorithm : 0.000101s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000022s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000061s : 0.00% jit_opt_a.merge_forward : 0.000074s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000068s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000153s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000162s : 0.00% jit_opt_a.meta_fg_expand : 0.426133s : 10.74% jit_opt_a.replace_old_param : 0.000251s : 0.01% jit_opt_a.inline_without_move : 0.000218s : 0.01% jit_opt_a.renormalize : 0.346300s : 8.72% jit_opt_a.add_forward_monad_depend : 0.000058s : 0.00% jit_opt_a.auto_monad_grad : 0.000030s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000273s : 0.01% jit_opt_a.cse : 0.000865s : 0.02% jit_opt_a.replace_applicator : 0.217657s : 5.48% py_interpret_to_execute_after_opt_a : 0.000024s : 0.00% rewriter_after_opt_a : 0.000376s : 0.01% convert_after_rewriter : 0.000020s : 0.00% order_py_execute_after_rewriter : 0.000010s : 0.00% mutable_eliminate : 0.000918s : 0.02% jit_opt_b.frontend_op_eliminate : 0.000220s : 0.01% jit_opt_b.inline_after_opt_a : 0.000066s : 0.00% cconv : 0.000042s : 0.00% loop_unroll : 0.000591s : 0.01% jit_opt_after_cconv.c_1 : 0.000067s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000017s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.cse : 0.000102s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000036s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000012s : 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 : 0.000045s : 0.00% remove_dup_value : 0.000069s : 0.00% partial_unused_args_eliminate : 0.000004s : 0.00% environ_conv : 0.000016s : 0.00% add_recomputation : 0.000101s : 0.00% cse_after_recomputation.cse : 0.000039s : 0.00% auto_monad_reorder : 0.000036s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.143413s : 3.61% symbol_engine_optimizer.build : 0.000024s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000016s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000035s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000020s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000077s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 1.940208s : 48.88% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.004527 361 0.53% : 0.000024s : 2: substitution.cast_eliminate 1.11% : 0.000050s : 15: substitution.depend_value_elim 0.10% : 0.000004s : 6: substitution.elim_not_effective 0.07% : 0.000003s : 6: substitution.fold_const_symbol 35.21% : 0.001594s : 9: substitution.getattr_setattr_resolve 0.20% : 0.000009s : 7: substitution.graph_param_transform 42.44% : 0.001921s : 32: substitution.inline 1.14% : 0.000052s : 5: substitution.inline_without_move 0.50% : 0.000023s : 40: substitution.j_node_and_user_rematch 0.60% : 0.000027s : 3: substitution.less_batch_normalization 0.95% : 0.000043s : 20: substitution.minmaximum_grad 0.39% : 0.000018s : 14: substitution.partial_eliminate 0.69% : 0.000031s : 40: substitution.remove_not_recompute_node 3.77% : 0.000171s : 25: substitution.replace_applicator 0.62% : 0.000028s : 20: substitution.replace_old_param 0.21% : 0.000009s : 2: substitution.set_cell_output_no_recompute 0.38% : 0.000017s : 3: substitution.switch_simplify 1.78% : 0.000081s : 20: substitution.tuple_list_convert_item_index_to_positive 1.49% : 0.000068s : 21: substitution.tuple_list_get_item_depend_reorder 3.30% : 0.000149s : 39: substitution.tuple_list_get_item_eliminator 0.87% : 0.000039s : 2: substitution.tuple_list_set_item_eliminator 0.70% : 0.000032s : 11: substitution.updatestate_pure_node_eliminater 1.58% : 0.000071s : 18: substitution.updatestate_useless_node_eliminater 1.36% : 0.000062s : 1: substitution.zero_like_fill_zero ------[type_inference.] 0.878791 2 99.64% : 0.875656s : 1: type_inference.infer 0.36% : 0.003134s : 1: type_inference.specialize ------[replace.] 0.001411 71 1.05% : 0.000015s : 2: replace.cast_eliminate 10.99% : 0.000155s : 7: replace.getattr_setattr_resolve 38.58% : 0.000544s : 32: replace.inline 10.53% : 0.000148s : 4: replace.replace_applicator 10.02% : 0.000141s : 3: replace.switch_simplify 0.82% : 0.000012s : 1: replace.tuple_list_get_item_depend_reorder 18.19% : 0.000257s : 18: replace.tuple_list_get_item_eliminator 2.92% : 0.000041s : 2: replace.tuple_list_set_item_eliminator 3.83% : 0.000054s : 1: replace.updatestate_useless_node_eliminater 3.07% : 0.000043s : 1: replace.zero_like_fill_zero ------[match.] 0.003628 71 0.57% : 0.000021s : 2: match.cast_eliminate 40.60% : 0.001473s : 7: match.getattr_setattr_resolve 52.21% : 0.001895s : 32: match.inline 1.36% : 0.000049s : 4: match.replace_applicator 0.42% : 0.000015s : 3: match.switch_simplify 0.42% : 0.000015s : 1: match.tuple_list_get_item_depend_reorder 1.39% : 0.000050s : 18: match.tuple_list_get_item_eliminator 0.96% : 0.000035s : 2: match.tuple_list_set_item_eliminator 0.40% : 0.000015s : 1: match.updatestate_useless_node_eliminater 1.66% : 0.000060s : 1: match.zero_like_fill_zero ------[predicate.] 0.001287 7225 1.32% : 0.000017s : 120: predicate.accumulaten_eliminater 0.68% : 0.000009s : 7: predicate.ad_related_special_op_eliminate 1.43% : 0.000018s : 120: predicate.addn_check_dump 1.41% : 0.000018s : 120: predicate.addn_zero_filter 1.84% : 0.000024s : 120: predicate.arithmetic_simplify 1.54% : 0.000020s : 122: predicate.cast_eliminate 0.21% : 0.000003s : 15: predicate.check_bprop_eliminate 1.33% : 0.000017s : 120: predicate.compare_switch_simplify 1.45% : 0.000019s : 120: predicate.depend_value_elim 1.34% : 0.000017s : 122: predicate.dict_get_item_const_eliminator 1.51% : 0.000019s : 122: predicate.dict_get_item_eliminator 1.31% : 0.000017s : 122: predicate.dict_set_item_eliminator 0.33% : 0.000004s : 7: predicate.dumpgradient_eliminate 0.09% : 0.000001s : 7: predicate.elim_not_effective 0.14% : 0.000002s : 7: predicate.elim_shapecalc_of_broadcastargs 1.32% : 0.000017s : 122: predicate.environ_add_const_eliminate 1.31% : 0.000017s : 122: predicate.environ_get_add_eliminate 1.31% : 0.000017s : 122: predicate.environ_get_depend_swap 1.36% : 0.000017s : 122: predicate.environ_get_eliminate 1.42% : 0.000018s : 122: predicate.environ_get_set_eliminate 0.05% : 0.000001s : 7: predicate.fold_const_symbol 0.62% : 0.000008s : 47: predicate.get_grad_eliminate 1.26% : 0.000016s : 51: predicate.getattr_setattr_resolve 0.05% : 0.000001s : 7: predicate.graph_param_transform 4.51% : 0.000058s : 196: predicate.inline 1.95% : 0.000025s : 130: predicate.inline_without_move 3.79% : 0.000049s : 47: predicate.j_node_and_user_rematch 0.77% : 0.000010s : 47: predicate.less_batch_normalization 1.64% : 0.000021s : 143: predicate.list_to_tuple_eliminator_ 1.77% : 0.000023s : 150: predicate.load_eliminater 0.28% : 0.000004s : 7: predicate.loop_unroll_after_grad 2.71% : 0.000035s : 208: predicate.loop_unroll_before_grad 1.62% : 0.000021s : 130: predicate.make_slice_get_slice_eliminator 1.23% : 0.000016s : 120: predicate.merge_addn 1.42% : 0.000018s : 120: predicate.minmaximum_grad 0.41% : 0.000005s : 9: predicate.mutable_eliminate 0.14% : 0.000002s : 7: predicate.opt_reshape 2.20% : 0.000028s : 150: predicate.partial_eliminate 1.35% : 0.000017s : 120: predicate.print_const_string_wrapper 1.83% : 0.000024s : 120: predicate.reduce_eliminate 1.69% : 0.000022s : 143: predicate.redundant_stop_gradient_eliminater 0.33% : 0.000004s : 47: predicate.remove_not_recompute_node 2.75% : 0.000035s : 300: predicate.replace_applicator 0.96% : 0.000012s : 130: predicate.replace_old_param 0.12% : 0.000002s : 14: predicate.reset_defer_inline 1.40% : 0.000018s : 120: predicate.reshape_eliminate 1.41% : 0.000018s : 120: predicate.row_tensor_add_zeros_like 0.28% : 0.000004s : 15: predicate.row_tensor_eliminate 1.57% : 0.000020s : 120: predicate.same_eliminate 2.07% : 0.000027s : 60: predicate.set_cell_output_no_recompute 0.31% : 0.000004s : 22: predicate.special_op_eliminate 0.87% : 0.000011s : 55: predicate.specialize_transform 1.76% : 0.000023s : 120: predicate.split_environ_get_set_with_tuple_value 1.47% : 0.000019s : 120: predicate.stack_unstack_eliminate 0.09% : 0.000001s : 7: predicate.switch_call_monad_eliminater 3.10% : 0.000040s : 175: predicate.switch_defer_inline 2.23% : 0.000029s : 175: predicate.switch_layer_defer_inline 5.53% : 0.000071s : 396: predicate.switch_simplify 1.54% : 0.000020s : 120: predicate.tile_eliminate 1.29% : 0.000017s : 120: predicate.transpose_eliminate 1.81% : 0.000023s : 122: predicate.tuple_list_convert_item_index_to_positive 1.75% : 0.000022s : 123: predicate.tuple_list_get_item_depend_reorder 3.59% : 0.000046s : 164: predicate.tuple_list_get_item_eliminator 1.84% : 0.000024s : 125: predicate.tuple_list_set_item_eliminator 1.69% : 0.000022s : 143: predicate.tuple_to_list_eliminator_ 1.72% : 0.000022s : 150: predicate.updatestate_pure_node_eliminater 2.55% : 0.000033s : 199: predicate.updatestate_useless_node_eliminater 1.65% : 0.000021s : 120: predicate.value_based_eliminate 0.11% : 0.000001s : 7: predicate.virtual_view_grad_eliminate 0.29% : 0.000004s : 16: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.111705 75 97.54% : 0.108955s : 31: func_graph_cloner_run.FuncGraphClonerGraph 0.42% : 0.000470s : 7: func_graph_cloner_run.FuncGraphClonerNode 2.04% : 0.002279s : 37: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 4.565542 114 0.00% : 0.000104s : 1: add_recomputation 0.01% : 0.000321s : 1: auto_monad 0.00% : 0.000040s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: backend_pass 0.01% : 0.000652s : 1: bootstrap 0.00% : 0.000046s : 1: cconv 0.00% : 0.000025s : 1: convert_after_rewriter 0.00% : 0.000059s : 1: cse_after_recomputation 0.00% : 0.000019s : 1: environ_conv 0.01% : 0.000231s : 1: event_method 0.00% : 0.000018s : 1: execute 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000015s : 1: graph_reusing 22.37% : 1.021159s : 1: jit_opt_a 0.01% : 0.000386s : 1: jit_opt_after_cconv 0.01% : 0.000344s : 1: jit_opt_b 0.01% : 0.000603s : 1: loop_unroll 0.02% : 0.000936s : 1: mutable_eliminate 5.00% : 0.228115s : 52: opt.transform.jit_opt_a 0.00% : 0.000155s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000267s : 8: opt.transform.jit_opt_b 0.00% : 0.000023s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000035s : 1: opt.transform.mutable_eliminate 0.00% : 0.000080s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.001900s : 4: opt.transform.opt_resolve 0.00% : 0.000079s : 4: opt.transform.symbol_engine_opt 3.14% : 0.143440s : 1: opt_after_jit_grad 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pre_auto_parallel 0.00% : 0.000066s : 1: py_interpret_to_execute 0.00% : 0.000027s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000073s : 1: remove_dup_value 7.43% : 0.339353s : 3: renormalize.infer 0.15% : 0.006902s : 3: renormalize.specialize 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000388s : 1: rewriter_after_opt_a 0.00% : 0.000171s : 1: rewriter_before_opt_a 0.00% : 0.000159s : 1: symbol_engine_optimizer 42.50% : 1.940229s : 1: task_emit 19.25% : 0.878950s : 1: type_inference 0.00% : 0.000120s : 1: validate . [hook] pytest_runtest_teardown:test_chunk_high_dimension[KBK] tests/st/mint/test_chunk.py::test_chunk_high_dimension[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 ================== 2 passed, 25 warnings in 214.45s (0:03:34) ==================