==================================================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_003/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_large_tensors[pynative] tests/st/mint/test_chunk.py::test_chunk_large_tensors[pynative],max_mem:2.0M TotalTime = 0.530614, [30] [bootstrap]: 0.00068629 [type_inference]: 0.38549 [event_method]: 1.544e-05 [auto_monad]: 0.00018336 [graph_reusing]: 7.01001e-06 [pre_auto_parallel]: 1.289e-05 [py_interpret_to_execute]: 0.00015346 [rewriter_before_opt_a]: 8.166e-05 [expand_dump_flag]: 4.28001e-06 [jit_opt_a]: 0.139821, [2] [Cycle 1]: 0.00283414, [27] [switch_simplify]: 8.28e-05 [loop_unroll]: 2.025e-05 [a_1]: 0.0005325 [with_stream_mark]: 3.734e-05 [recompute_prepare]: 1.671e-05 [updatestate_depend_eliminate]: 8.62e-06 [updatestate_assign_eliminate]: 6.21e-06 [updatestate_loads_eliminate]: 5.46e-06 [parameter_eliminate]: 2.31e-06 [specialize_transform]: 1.211e-05 [updatestate_useless_node_eliminater]: 1.256e-05 [accelerated_algorithm]: 1.037e-05 [meta_shard_fg_expand]: 3.86999e-06 [get_grad_eliminate_]: 9.17001e-06 [merge_forward]: 5.94e-06 [cell_reuse_recompute_pass]: 1.60001e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.026e-05 [j_node_and_user_rematch]: 1.674e-05 [meta_fg_expand]: 3.84002e-06 [replace_old_param]: 1.453e-05 [inline_without_move]: 8.46002e-06 [renormalize]: 0.0015757 [add_forward_monad_depend]: 1.785e-05 [auto_monad_grad]: 3.67002e-06 [auto_monad_eliminator]: 3.078e-05 [cse]: 4.832e-05 [replace_applicator]: 2.967e-05 [Cycle 2]: 0.00061452, [27] [switch_simplify]: 9.50001e-06 [loop_unroll]: 9.08002e-06 [a_1]: 0.00019167 [with_stream_mark]: 2.286e-05 [recompute_prepare]: 9.88002e-06 [updatestate_depend_eliminate]: 7.63999e-06 [updatestate_assign_eliminate]: 6.97002e-06 [updatestate_loads_eliminate]: 4.77998e-06 [parameter_eliminate]: 1.86e-06 [specialize_transform]: 9.63002e-06 [updatestate_useless_node_eliminater]: 1.201e-05 [accelerated_algorithm]: 9.68002e-06 [meta_shard_fg_expand]: 2.91999e-06 [get_grad_eliminate_]: 7.88999e-06 [merge_forward]: 7.65998e-06 [cell_reuse_recompute_pass]: 3.77002e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.254e-05 [j_node_and_user_rematch]: 1.526e-05 [meta_fg_expand]: 4.42e-06 [replace_old_param]: 1.522e-05 [inline_without_move]: 9.14998e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.67001e-06 [auto_monad_grad]: 1.47001e-06 [auto_monad_eliminator]: 1.303e-05 [cse]: 2.648e-05 [replace_applicator]: 2.954e-05 [py_interpret_to_execute_after_opt_a]: 2.168e-05 [rewriter_after_opt_a]: 0.00033243 [convert_after_rewriter]: 1.894e-05 [order_py_execute_after_rewriter]: 8.59998e-06 [mutable_eliminate]: 0.00085622 [jit_opt_b]: 8.632e-05, [1] [Cycle 1]: 7.429e-05, [2] [frontend_op_eliminate]: 2.828e-05 [inline_after_opt_a]: 2.952e-05 [cconv]: 4.436e-05 [loop_unroll]: 0.00051837 [jit_opt_after_cconv]: 0.00027257, [1] [Cycle 1]: 0.00026321, [11] [c_1]: 5.766e-05 [parameter_eliminate]: 6.58e-06 [updatestate_depend_eliminate]: 1.467e-05 [updatestate_assign_eliminate]: 6.04999e-06 [updatestate_loads_eliminate]: 5.69e-06 [cse]: 5.336e-05 [call_graph_tuple_transform]: 2.913e-05 [tuple_list_get_item_eliminator]: 1.014e-05 [none_parameter_eliminate]: 2.12001e-06 [renormalize]: 7.2e-07 [switch_simplify]: 1.015e-05 [remove_dup_value]: 2.581e-05 [partial_unused_args_eliminate]: 2.37001e-06 [environ_conv]: 4.157e-05 [add_recomputation]: 0.00010772 [cse_after_recomputation]: 5.108e-05, [1] [Cycle 1]: 3.988e-05, [1] [cse]: 2.64e-05 [auto_monad_reorder]: 4.919e-05 [get_jit_bprop_graph]: 3.23e-06 [rewriter_after_jit_bprop_graph]: 0.00020602 [opt_after_jit_grad]: 0.00085967 [symbol_engine_optimizer]: 0.00014459, [1] [Cycle 1]: 0.00013264, [6] [build]: 2.681e-05 [elim_shapecalc]: 1.41e-05 [elim_not_effective]: 2.722e-05 [opt_reshape]: 1.043e-05 [fold_const_symbol]: 1.548e-05 [renormalize]: 8.39995e-07 [validate]: 0.00010436 Sums bootstrap : 0.000686s : 0.17% type_inference : 0.385490s : 98.03% event_method : 0.000015s : 0.00% auto_monad : 0.000183s : 0.05% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000013s : 0.00% py_interpret_to_execute : 0.000153s : 0.04% rewriter_before_opt_a : 0.000082s : 0.02% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000092s : 0.02% jit_opt_a.loop_unroll : 0.000029s : 0.01% jit_opt_a.a_1 : 0.000724s : 0.18% jit_opt_a.with_stream_mark : 0.000060s : 0.02% jit_opt_a.recompute_prepare : 0.000027s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000016s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000022s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000025s : 0.01% jit_opt_a.accelerated_algorithm : 0.000020s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000007s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000017s : 0.00% jit_opt_a.merge_forward : 0.000014s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000073s : 0.02% jit_opt_a.j_node_and_user_rematch : 0.000032s : 0.01% jit_opt_a.meta_fg_expand : 0.000008s : 0.00% jit_opt_a.replace_old_param : 0.000030s : 0.01% jit_opt_a.inline_without_move : 0.000018s : 0.00% jit_opt_a.renormalize : 0.001576s : 0.40% jit_opt_a.add_forward_monad_depend : 0.000020s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000044s : 0.01% jit_opt_a.cse : 0.000075s : 0.02% jit_opt_a.replace_applicator : 0.000059s : 0.02% py_interpret_to_execute_after_opt_a : 0.000022s : 0.01% rewriter_after_opt_a : 0.000332s : 0.08% convert_after_rewriter : 0.000019s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.000856s : 0.22% jit_opt_b.frontend_op_eliminate : 0.000028s : 0.01% jit_opt_b.inline_after_opt_a : 0.000030s : 0.01% cconv : 0.000044s : 0.01% loop_unroll : 0.000518s : 0.13% jit_opt_after_cconv.c_1 : 0.000058s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000015s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.cse : 0.000053s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000029s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000010s : 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 : 0.000010s : 0.00% remove_dup_value : 0.000026s : 0.01% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000042s : 0.01% add_recomputation : 0.000108s : 0.03% cse_after_recomputation.cse : 0.000026s : 0.01% auto_monad_reorder : 0.000049s : 0.01% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000206s : 0.05% opt_after_jit_grad : 0.000860s : 0.22% symbol_engine_optimizer.build : 0.000027s : 0.01% symbol_engine_optimizer.elim_shapecalc : 0.000014s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000027s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000015s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000104s : 0.03% Time group info: ------[substitution.] 0.000297 43 4.35% : 0.000013s : 2: substitution.depend_value_elim 1.63% : 0.000005s : 4: substitution.elim_not_effective 0.84% : 0.000002s : 4: substitution.fold_const_symbol 2.61% : 0.000008s : 5: substitution.graph_param_transform 66.84% : 0.000199s : 2: substitution.inline 1.91% : 0.000006s : 8: substitution.j_node_and_user_rematch 10.11% : 0.000030s : 8: substitution.remove_not_recompute_node 2.55% : 0.000008s : 2: substitution.replace_old_param 5.11% : 0.000015s : 3: substitution.updatestate_pure_node_eliminater 4.07% : 0.000012s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.385405 2 99.67% : 0.384134s : 1: type_inference.infer 0.33% : 0.001271s : 1: type_inference.specialize ------[replace.] 0.000040 2 100.00% : 0.000040s : 2: replace.inline ------[match.] 0.000197 2 100.00% : 0.000197s : 2: match.inline ------[predicate.] 0.000164 767 1.20% : 0.000002s : 11: predicate.accumulaten_eliminater 2.89% : 0.000005s : 5: predicate.ad_related_special_op_eliminate 0.92% : 0.000002s : 11: predicate.addn_check_dump 1.32% : 0.000002s : 11: predicate.addn_zero_filter 2.53% : 0.000004s : 11: predicate.arithmetic_simplify 1.15% : 0.000002s : 11: predicate.cast_eliminate 0.50% : 0.000001s : 5: predicate.check_bprop_eliminate 1.00% : 0.000002s : 11: predicate.compare_switch_simplify 1.23% : 0.000002s : 11: predicate.depend_value_elim 1.10% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.21% : 0.000002s : 11: predicate.dict_get_item_eliminator 0.98% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.82% : 0.000003s : 5: predicate.dumpgradient_eliminate 0.62% : 0.000001s : 5: predicate.elim_not_effective 0.79% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.12% : 0.000002s : 11: predicate.environ_add_const_eliminate 0.90% : 0.000001s : 11: predicate.environ_get_add_eliminate 0.96% : 0.000002s : 11: predicate.environ_get_depend_swap 1.06% : 0.000002s : 11: predicate.environ_get_eliminate 0.90% : 0.000001s : 11: predicate.environ_get_set_eliminate 0.26% : 0.000000s : 5: predicate.fold_const_symbol 1.47% : 0.000002s : 10: predicate.get_grad_eliminate 0.30% : 0.000000s : 5: predicate.graph_param_transform 5.60% : 0.000009s : 23: predicate.inline 1.35% : 0.000002s : 10: predicate.inline_without_move 0.49% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.74% : 0.000003s : 10: predicate.less_batch_normalization 1.36% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.64% : 0.000003s : 16: predicate.load_eliminater 2.02% : 0.000003s : 5: predicate.loop_unroll_after_grad 2.36% : 0.000004s : 20: predicate.loop_unroll_before_grad 2.08% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 0.96% : 0.000002s : 11: predicate.merge_addn 0.93% : 0.000002s : 11: predicate.minmaximum_grad 3.09% : 0.000005s : 5: predicate.mutable_eliminate 0.55% : 0.000001s : 5: predicate.opt_reshape 1.98% : 0.000003s : 16: predicate.partial_eliminate 1.18% : 0.000002s : 11: predicate.print_const_string_wrapper 1.84% : 0.000003s : 11: predicate.reduce_eliminate 1.07% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.93% : 0.000002s : 10: predicate.remove_not_recompute_node 1.84% : 0.000003s : 21: predicate.replace_applicator 1.21% : 0.000002s : 10: predicate.replace_old_param 0.53% : 0.000001s : 5: predicate.reset_defer_inline 1.14% : 0.000002s : 11: predicate.reshape_eliminate 1.18% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.92% : 0.000002s : 5: predicate.row_tensor_eliminate 1.15% : 0.000002s : 11: predicate.same_eliminate 0.61% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.18% : 0.000002s : 10: predicate.special_op_eliminate 1.31% : 0.000002s : 10: predicate.specialize_transform 1.37% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.20% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.63% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.68% : 0.000003s : 13: predicate.switch_defer_inline 1.35% : 0.000002s : 13: predicate.switch_layer_defer_inline 5.82% : 0.000010s : 38: predicate.switch_simplify 1.07% : 0.000002s : 11: predicate.tile_eliminate 1.23% : 0.000002s : 11: predicate.transpose_eliminate 1.56% : 0.000003s : 11: predicate.tuple_list_convert_item_index_to_positive 1.10% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.92% : 0.000006s : 21: predicate.tuple_list_get_item_eliminator 1.61% : 0.000003s : 11: predicate.tuple_list_set_item_eliminator 1.34% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.61% : 0.000003s : 16: predicate.updatestate_pure_node_eliminater 2.99% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.81% : 0.000003s : 11: predicate.value_based_eliminate 0.47% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.73% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000558 6 31.19% : 0.000174s : 2: func_graph_cloner_run.FuncGraphClonerGraph 68.81% : 0.000384s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.533286 72 0.02% : 0.000112s : 1: add_recomputation 0.04% : 0.000189s : 1: auto_monad 0.01% : 0.000053s : 1: auto_monad_reorder 0.13% : 0.000714s : 1: bootstrap 0.01% : 0.000047s : 1: cconv 0.00% : 0.000023s : 1: convert_after_rewriter 0.01% : 0.000055s : 1: cse_after_recomputation 0.01% : 0.000046s : 1: environ_conv 0.00% : 0.000021s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 26.22% : 0.139827s : 1: jit_opt_a 0.05% : 0.000277s : 1: jit_opt_after_cconv 0.02% : 0.000090s : 1: jit_opt_b 0.10% : 0.000531s : 1: loop_unroll 0.16% : 0.000873s : 1: mutable_eliminate 0.21% : 0.001105s : 26: opt.transform.jit_opt_a 0.02% : 0.000102s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000048s : 4: opt.transform.jit_opt_b 0.00% : 0.000021s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000032s : 1: opt.transform.mutable_eliminate 0.01% : 0.000050s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000063s : 4: opt.transform.symbol_engine_opt 0.17% : 0.000883s : 1: opt_after_jit_grad 0.00% : 0.000011s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000016s : 1: pre_auto_parallel 0.03% : 0.000158s : 1: py_interpret_to_execute 0.00% : 0.000025s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000028s : 1: remove_dup_value 0.19% : 0.001019s : 1: renormalize.infer 0.10% : 0.000540s : 1: renormalize.specialize 0.04% : 0.000214s : 1: rewriter_after_jit_bprop_graph 0.06% : 0.000340s : 1: rewriter_after_opt_a 0.02% : 0.000087s : 1: rewriter_before_opt_a 0.03% : 0.000149s : 1: symbol_engine_optimizer 72.29% : 0.385509s : 1: type_inference TotalTime = 1.77655, [30] [bootstrap]: 0.00058079 [type_inference]: 0.66318 [event_method]: 0.00075137 [auto_monad]: 0.00043954 [graph_reusing]: 1.399e-05 [pre_auto_parallel]: 4.55001e-06 [py_interpret_to_execute]: 8.392e-05 [rewriter_before_opt_a]: 0.0002297 [expand_dump_flag]: 4.76002e-06 [jit_opt_a]: 1.01452, [4] [Cycle 1]: 0.827229, [27] [switch_simplify]: 0.0002746 [loop_unroll]: 6.482e-05 [a_1]: 0.00220033 [with_stream_mark]: 5.97e-05 [recompute_prepare]: 4.946e-05 [updatestate_depend_eliminate]: 6.171e-05 [updatestate_assign_eliminate]: 1.252e-05 [updatestate_loads_eliminate]: 1.084e-05 [parameter_eliminate]: 4.86002e-06 [specialize_transform]: 2.628e-05 [updatestate_useless_node_eliminater]: 2.873e-05 [accelerated_algorithm]: 2.247e-05 [meta_shard_fg_expand]: 9.51003e-06 [get_grad_eliminate_]: 2.046e-05 [merge_forward]: 1.46e-05 [cell_reuse_recompute_pass]: 1.72001e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.689e-05 [j_node_and_user_rematch]: 4.182e-05 [meta_fg_expand]: 0.401681 [replace_old_param]: 0.00018086 [inline_without_move]: 0.00016484 [renormalize]: 0.298131 [add_forward_monad_depend]: 7.417e-05 [auto_monad_grad]: 7.416e-05 [auto_monad_eliminator]: 0.00035954 [cse]: 0.00070042 [replace_applicator]: 0.00051537 [Cycle 2]: 0.0149396, [27] [switch_simplify]: 0.00013339 [loop_unroll]: 0.00011895 [a_1]: 0.00848507 [with_stream_mark]: 0.00010797 [recompute_prepare]: 6.961e-05 [updatestate_depend_eliminate]: 2.978e-05 [updatestate_assign_eliminate]: 2.534e-05 [updatestate_loads_eliminate]: 2.395e-05 [parameter_eliminate]: 7.73001e-06 [specialize_transform]: 4.274e-05 [updatestate_useless_node_eliminater]: 0.00017943 [accelerated_algorithm]: 6.277e-05 [meta_shard_fg_expand]: 1.547e-05 [get_grad_eliminate_]: 2.643e-05 [merge_forward]: 1.447e-05 [cell_reuse_recompute_pass]: 2.02001e-06 [cell_reuse_handle_not_recompute_node_pass]: 5.683e-05 [j_node_and_user_rematch]: 4.684e-05 [meta_fg_expand]: 0.00027581 [replace_old_param]: 6.976e-05 [inline_without_move]: 2.849e-05 [renormalize]: 0.00400003 [add_forward_monad_depend]: 1.296e-05 [auto_monad_grad]: 3.52997e-06 [auto_monad_eliminator]: 5.336e-05 [cse]: 0.00061302 [replace_applicator]: 5.115e-05 [Cycle 3]: 0.00393238, [27] [switch_simplify]: 2.868e-05 [loop_unroll]: 2.251e-05 [a_1]: 0.00071311 [with_stream_mark]: 4.238e-05 [recompute_prepare]: 2.45e-05 [updatestate_depend_eliminate]: 6.71e-05 [updatestate_assign_eliminate]: 1.263e-05 [updatestate_loads_eliminate]: 1.071e-05 [parameter_eliminate]: 3.42002e-06 [specialize_transform]: 2.302e-05 [updatestate_useless_node_eliminater]: 2.601e-05 [accelerated_algorithm]: 2.751e-05 [meta_shard_fg_expand]: 7.83999e-06 [get_grad_eliminate_]: 1.813e-05 [merge_forward]: 1.167e-05 [cell_reuse_recompute_pass]: 3.93999e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.677e-05 [j_node_and_user_rematch]: 3.604e-05 [meta_fg_expand]: 8.61002e-06 [replace_old_param]: 2.705e-05 [inline_without_move]: 1.912e-05 [renormalize]: 0.00225555 [add_forward_monad_depend]: 9.82999e-06 [auto_monad_grad]: 2.49001e-06 [auto_monad_eliminator]: 4.027e-05 [cse]: 0.00017972 [replace_applicator]: 3.858e-05 [Cycle 4]: 0.163622, [27] [switch_simplify]: 2.025e-05 [loop_unroll]: 1.986e-05 [a_1]: 0.00056821 [with_stream_mark]: 2.794e-05 [recompute_prepare]: 9.959e-05 [updatestate_depend_eliminate]: 4.037e-05 [updatestate_assign_eliminate]: 1.264e-05 [updatestate_loads_eliminate]: 1.549e-05 [parameter_eliminate]: 8.89e-06 [specialize_transform]: 2.522e-05 [updatestate_useless_node_eliminater]: 4.02e-05 [accelerated_algorithm]: 3.65e-05 [meta_shard_fg_expand]: 1.247e-05 [get_grad_eliminate_]: 1.903e-05 [merge_forward]: 1.315e-05 [cell_reuse_recompute_pass]: 4.28999e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.785e-05 [j_node_and_user_rematch]: 3.553e-05 [meta_fg_expand]: 8.33001e-06 [replace_old_param]: 2.55e-05 [inline_without_move]: 2.828e-05 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 6.78998e-06 [auto_monad_grad]: 4.08001e-06 [auto_monad_eliminator]: 8.332e-05 [cse]: 0.00013718 [replace_applicator]: 2.435e-05 [py_interpret_to_execute_after_opt_a]: 4.479e-05 [rewriter_after_opt_a]: 0.00054125 [convert_after_rewriter]: 2.977e-05 [order_py_execute_after_rewriter]: 1.503e-05 [mutable_eliminate]: 0.00103519 [jit_opt_b]: 0.00046225, [2] [Cycle 1]: 0.00037701, [2] [frontend_op_eliminate]: 0.00031214 [inline_after_opt_a]: 3.956e-05 [Cycle 2]: 6.73e-05, [2] [frontend_op_eliminate]: 2.694e-05 [inline_after_opt_a]: 2.74e-05 [cconv]: 4.595e-05 [loop_unroll]: 0.00055938 [jit_opt_after_cconv]: 0.00032859, [1] [Cycle 1]: 0.00032034, [11] [c_1]: 6.716e-05 [parameter_eliminate]: 6.44999e-06 [updatestate_depend_eliminate]: 1.994e-05 [updatestate_assign_eliminate]: 7.78001e-06 [updatestate_loads_eliminate]: 6.84999e-06 [cse]: 8.052e-05 [call_graph_tuple_transform]: 3.476e-05 [tuple_list_get_item_eliminator]: 1.262e-05 [none_parameter_eliminate]: 1.89999e-06 [renormalize]: 7.7e-07 [switch_simplify]: 1.287e-05 [remove_dup_value]: 9.779e-05 [partial_unused_args_eliminate]: 3.36999e-06 [environ_conv]: 1.757e-05 [add_recomputation]: 0.00010528 [cse_after_recomputation]: 5.067e-05, [1] [Cycle 1]: 4.311e-05, [1] [cse]: 3.494e-05 [auto_monad_reorder]: 3.457e-05 [get_jit_bprop_graph]: 2.83e-06 [rewriter_after_jit_bprop_graph]: 1.026e-05 [opt_after_jit_grad]: 0.00072184 [symbol_engine_optimizer]: 0.00014086, [1] [Cycle 1]: 0.00013305, [6] [build]: 2.045e-05 [elim_shapecalc]: 1.65e-05 [elim_not_effective]: 2.898e-05 [opt_reshape]: 1.31e-05 [fold_const_symbol]: 2.017e-05 [renormalize]: 5.09986e-07 [validate]: 6.951e-05 Sums bootstrap : 0.000581s : 0.04% type_inference : 0.663180s : 47.58% event_method : 0.000751s : 0.05% auto_monad : 0.000440s : 0.03% graph_reusing : 0.000014s : 0.00% pre_auto_parallel : 0.000005s : 0.00% py_interpret_to_execute : 0.000084s : 0.01% rewriter_before_opt_a : 0.000230s : 0.02% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000457s : 0.03% jit_opt_a.loop_unroll : 0.000226s : 0.02% jit_opt_a.a_1 : 0.011967s : 0.86% jit_opt_a.with_stream_mark : 0.000238s : 0.02% jit_opt_a.recompute_prepare : 0.000243s : 0.02% jit_opt_a.updatestate_depend_eliminate : 0.000199s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000063s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000061s : 0.00% jit_opt_a.parameter_eliminate : 0.000025s : 0.00% jit_opt_a.specialize_transform : 0.000117s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000274s : 0.02% jit_opt_a.accelerated_algorithm : 0.000149s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000045s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000084s : 0.01% jit_opt_a.merge_forward : 0.000054s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000012s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000198s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000160s : 0.01% jit_opt_a.meta_fg_expand : 0.401974s : 28.84% jit_opt_a.replace_old_param : 0.000303s : 0.02% jit_opt_a.inline_without_move : 0.000241s : 0.02% jit_opt_a.renormalize : 0.304387s : 21.84% jit_opt_a.add_forward_monad_depend : 0.000104s : 0.01% jit_opt_a.auto_monad_grad : 0.000084s : 0.01% jit_opt_a.auto_monad_eliminator : 0.000536s : 0.04% jit_opt_a.cse : 0.001630s : 0.12% jit_opt_a.replace_applicator : 0.000629s : 0.05% py_interpret_to_execute_after_opt_a : 0.000045s : 0.00% rewriter_after_opt_a : 0.000541s : 0.04% convert_after_rewriter : 0.000030s : 0.00% order_py_execute_after_rewriter : 0.000015s : 0.00% mutable_eliminate : 0.001035s : 0.07% jit_opt_b.frontend_op_eliminate : 0.000339s : 0.02% jit_opt_b.inline_after_opt_a : 0.000067s : 0.00% cconv : 0.000046s : 0.00% loop_unroll : 0.000559s : 0.04% jit_opt_after_cconv.c_1 : 0.000067s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000020s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.cse : 0.000081s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000035s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000013s : 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 : 0.000013s : 0.00% remove_dup_value : 0.000098s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000018s : 0.00% add_recomputation : 0.000105s : 0.01% cse_after_recomputation.cse : 0.000035s : 0.00% auto_monad_reorder : 0.000035s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.000722s : 0.05% symbol_engine_optimizer.build : 0.000020s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000029s : 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 : 0.000070s : 0.00% Time group info: ------[substitution.] 0.006332 463 0.95% : 0.000060s : 8: substitution.cast_eliminate 0.92% : 0.000058s : 15: substitution.depend_value_elim 0.07% : 0.000004s : 6: substitution.elim_not_effective 0.05% : 0.000003s : 6: substitution.fold_const_symbol 30.10% : 0.001906s : 9: substitution.getattr_setattr_resolve 0.15% : 0.000010s : 7: substitution.graph_param_transform 49.69% : 0.003146s : 38: substitution.inline 0.81% : 0.000051s : 5: substitution.inline_without_move 0.46% : 0.000029s : 58: substitution.j_node_and_user_rematch 0.56% : 0.000036s : 3: substitution.less_batch_normalization 0.97% : 0.000061s : 32: substitution.minmaximum_grad 0.24% : 0.000015s : 14: substitution.partial_eliminate 0.62% : 0.000039s : 58: substitution.remove_not_recompute_node 2.25% : 0.000143s : 28: substitution.replace_applicator 0.45% : 0.000029s : 20: substitution.replace_old_param 0.18% : 0.000011s : 2: substitution.set_cell_output_no_recompute 0.30% : 0.000019s : 3: substitution.switch_simplify 1.80% : 0.000114s : 32: substitution.tuple_list_convert_item_index_to_positive 1.57% : 0.000099s : 33: substitution.tuple_list_get_item_depend_reorder 3.31% : 0.000210s : 51: substitution.tuple_list_get_item_eliminator 0.74% : 0.000047s : 2: substitution.tuple_list_set_item_eliminator 0.56% : 0.000035s : 11: substitution.updatestate_pure_node_eliminater 1.25% : 0.000079s : 18: substitution.updatestate_useless_node_eliminater 2.02% : 0.000128s : 4: substitution.zero_like_fill_zero ------[type_inference.] 0.662984 2 99.33% : 0.658573s : 1: type_inference.infer 0.67% : 0.004411s : 1: type_inference.specialize ------[replace.] 0.002067 89 3.43% : 0.000071s : 8: replace.cast_eliminate 9.35% : 0.000193s : 7: replace.getattr_setattr_resolve 42.12% : 0.000871s : 38: replace.inline 7.27% : 0.000150s : 7: replace.replace_applicator 4.41% : 0.000091s : 3: replace.switch_simplify 0.78% : 0.000016s : 1: replace.tuple_list_get_item_depend_reorder 18.88% : 0.000390s : 18: replace.tuple_list_get_item_eliminator 3.61% : 0.000075s : 2: replace.tuple_list_set_item_eliminator 5.36% : 0.000111s : 1: replace.updatestate_useless_node_eliminater 4.80% : 0.000099s : 4: replace.zero_like_fill_zero ------[match.] 0.005176 89 1.02% : 0.000053s : 8: match.cast_eliminate 32.28% : 0.001671s : 7: match.getattr_setattr_resolve 60.07% : 0.003109s : 38: match.inline 0.95% : 0.000049s : 7: match.replace_applicator 0.32% : 0.000016s : 3: match.switch_simplify 0.36% : 0.000019s : 1: match.tuple_list_get_item_depend_reorder 1.41% : 0.000073s : 18: match.tuple_list_get_item_eliminator 0.84% : 0.000043s : 2: match.tuple_list_set_item_eliminator 0.35% : 0.000018s : 1: match.updatestate_useless_node_eliminater 2.41% : 0.000125s : 4: match.zero_like_fill_zero ------[predicate.] 0.001720 8974 1.27% : 0.000022s : 150: predicate.accumulaten_eliminater 0.18% : 0.000003s : 7: predicate.ad_related_special_op_eliminate 1.21% : 0.000021s : 150: predicate.addn_check_dump 1.29% : 0.000022s : 150: predicate.addn_zero_filter 2.08% : 0.000036s : 150: predicate.arithmetic_simplify 1.43% : 0.000025s : 158: predicate.cast_eliminate 0.13% : 0.000002s : 15: predicate.check_bprop_eliminate 1.29% : 0.000022s : 150: predicate.compare_switch_simplify 1.40% : 0.000024s : 150: predicate.depend_value_elim 3.48% : 0.000060s : 158: predicate.dict_get_item_const_eliminator 1.47% : 0.000025s : 158: predicate.dict_get_item_eliminator 1.43% : 0.000025s : 158: predicate.dict_set_item_eliminator 0.13% : 0.000002s : 7: predicate.dumpgradient_eliminate 0.07% : 0.000001s : 7: predicate.elim_not_effective 0.10% : 0.000002s : 7: predicate.elim_shapecalc_of_broadcastargs 1.32% : 0.000023s : 158: predicate.environ_add_const_eliminate 2.54% : 0.000044s : 158: predicate.environ_get_add_eliminate 1.26% : 0.000022s : 158: predicate.environ_get_depend_swap 1.53% : 0.000026s : 158: predicate.environ_get_eliminate 1.32% : 0.000023s : 158: predicate.environ_get_set_eliminate 0.03% : 0.000001s : 7: predicate.fold_const_symbol 0.68% : 0.000012s : 65: predicate.get_grad_eliminate 1.22% : 0.000021s : 51: predicate.getattr_setattr_resolve 0.03% : 0.000001s : 7: predicate.graph_param_transform 4.07% : 0.000070s : 238: predicate.inline 1.64% : 0.000028s : 148: predicate.inline_without_move 0.27% : 0.000005s : 65: predicate.j_node_and_user_rematch 0.95% : 0.000016s : 65: predicate.less_batch_normalization 1.78% : 0.000031s : 179: predicate.list_to_tuple_eliminator_ 1.58% : 0.000027s : 186: predicate.load_eliminater 0.17% : 0.000003s : 7: predicate.loop_unroll_after_grad 2.02% : 0.000035s : 226: predicate.loop_unroll_before_grad 1.52% : 0.000026s : 166: predicate.make_slice_get_slice_eliminator 4.46% : 0.000077s : 150: predicate.merge_addn 1.29% : 0.000022s : 150: predicate.minmaximum_grad 0.50% : 0.000009s : 15: predicate.mutable_eliminate 0.08% : 0.000001s : 7: predicate.opt_reshape 2.24% : 0.000039s : 186: predicate.partial_eliminate 1.23% : 0.000021s : 150: predicate.print_const_string_wrapper 1.63% : 0.000028s : 150: predicate.reduce_eliminate 1.52% : 0.000026s : 179: predicate.redundant_stop_gradient_eliminater 0.35% : 0.000006s : 65: predicate.remove_not_recompute_node 2.21% : 0.000038s : 366: predicate.replace_applicator 0.79% : 0.000014s : 148: predicate.replace_old_param 0.07% : 0.000001s : 14: predicate.reset_defer_inline 1.35% : 0.000023s : 150: predicate.reshape_eliminate 1.22% : 0.000021s : 150: predicate.row_tensor_add_zeros_like 0.19% : 0.000003s : 15: predicate.row_tensor_eliminate 1.42% : 0.000024s : 150: predicate.same_eliminate 0.55% : 0.000009s : 84: predicate.set_cell_output_no_recompute 0.25% : 0.000004s : 22: predicate.special_op_eliminate 1.03% : 0.000018s : 79: predicate.specialize_transform 5.15% : 0.000089s : 150: predicate.split_environ_get_set_with_tuple_value 1.28% : 0.000022s : 150: predicate.stack_unstack_eliminate 0.09% : 0.000002s : 7: predicate.switch_call_monad_eliminater 3.94% : 0.000068s : 217: predicate.switch_defer_inline 3.01% : 0.000052s : 217: predicate.switch_layer_defer_inline 4.69% : 0.000081s : 456: predicate.switch_simplify 1.23% : 0.000021s : 150: predicate.tile_eliminate 1.38% : 0.000024s : 150: predicate.transpose_eliminate 1.79% : 0.000031s : 158: predicate.tuple_list_convert_item_index_to_positive 1.67% : 0.000029s : 159: predicate.tuple_list_get_item_depend_reorder 3.15% : 0.000054s : 200: predicate.tuple_list_get_item_eliminator 1.68% : 0.000029s : 161: predicate.tuple_list_set_item_eliminator 1.52% : 0.000026s : 179: predicate.tuple_to_list_eliminator_ 1.54% : 0.000026s : 186: predicate.updatestate_pure_node_eliminater 2.52% : 0.000043s : 253: predicate.updatestate_useless_node_eliminater 1.74% : 0.000030s : 150: predicate.value_based_eliminate 0.06% : 0.000001s : 7: predicate.virtual_view_grad_eliminate 0.29% : 0.000005s : 19: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.007900 81 52.31% : 0.004132s : 31: func_graph_cloner_run.FuncGraphClonerGraph 11.39% : 0.000900s : 13: func_graph_cloner_run.FuncGraphClonerNode 36.30% : 0.002867s : 37: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.098645 110 0.01% : 0.000109s : 1: add_recomputation 0.02% : 0.000451s : 1: auto_monad 0.00% : 0.000038s : 1: auto_monad_reorder 0.03% : 0.000605s : 1: bootstrap 0.00% : 0.000050s : 1: cconv 0.00% : 0.000034s : 1: convert_after_rewriter 0.00% : 0.000054s : 1: cse_after_recomputation 0.00% : 0.000021s : 1: environ_conv 0.04% : 0.000784s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000018s : 1: graph_reusing 48.34% : 1.014528s : 1: jit_opt_a 0.02% : 0.000332s : 1: jit_opt_after_cconv 0.02% : 0.000466s : 1: jit_opt_b 0.03% : 0.000569s : 1: loop_unroll 0.05% : 0.001049s : 1: mutable_eliminate 0.71% : 0.014918s : 52: opt.transform.jit_opt_a 0.01% : 0.000122s : 4: opt.transform.jit_opt_after_cconv 0.02% : 0.000389s : 8: opt.transform.jit_opt_b 0.00% : 0.000024s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000046s : 1: opt.transform.mutable_eliminate 0.00% : 0.000052s : 1: opt.transform.opt_after_jit_grad 0.11% : 0.002302s : 4: opt.transform.opt_resolve 0.00% : 0.000073s : 4: opt.transform.symbol_engine_opt 0.03% : 0.000734s : 1: opt_after_jit_grad 0.00% : 0.000018s : 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% : 0.000089s : 1: py_interpret_to_execute 0.00% : 0.000048s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000102s : 1: remove_dup_value 14.05% : 0.294841s : 3: renormalize.infer 0.45% : 0.009494s : 3: renormalize.specialize 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.03% : 0.000550s : 1: rewriter_after_opt_a 0.01% : 0.000234s : 1: rewriter_before_opt_a 0.01% : 0.000145s : 1: symbol_engine_optimizer 35.99% : 0.755318s : 1: type_inference . [hook] pytest_runtest_teardown:test_chunk_large_tensors[KBK] tests/st/mint/test_chunk.py::test_chunk_large_tensors[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 103.37s (0:01:43) ==================