==================================================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_008/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_single_chunk[pynative] tests/st/mint/test_chunk.py::test_chunk_single_chunk[pynative],max_mem:2.0M TotalTime = 0.172665, [30] [bootstrap]: 0.00066487 [type_inference]: 0.135867 [event_method]: 1.773e-05 [auto_monad]: 0.00016476 [graph_reusing]: 5.96e-06 [pre_auto_parallel]: 1.085e-05 [py_interpret_to_execute]: 8.887e-05 [rewriter_before_opt_a]: 6.924e-05 [expand_dump_flag]: 2.98e-06 [jit_opt_a]: 0.0328228, [2] [Cycle 1]: 0.00186624, [27] [switch_simplify]: 5.794e-05 [loop_unroll]: 2.159e-05 [a_1]: 0.0003865 [with_stream_mark]: 2.482e-05 [recompute_prepare]: 9.70002e-06 [updatestate_depend_eliminate]: 7.87998e-06 [updatestate_assign_eliminate]: 8.35001e-06 [updatestate_loads_eliminate]: 4.67e-06 [parameter_eliminate]: 1.87999e-06 [specialize_transform]: 8.62998e-06 [updatestate_useless_node_eliminater]: 1.166e-05 [accelerated_algorithm]: 8.52e-06 [meta_shard_fg_expand]: 2.76e-06 [get_grad_eliminate_]: 8.32003e-06 [merge_forward]: 5.62999e-06 [cell_reuse_recompute_pass]: 1.29e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.254e-05 [j_node_and_user_rematch]: 1.346e-05 [meta_fg_expand]: 3.48e-06 [replace_old_param]: 1.301e-05 [inline_without_move]: 7.98001e-06 [renormalize]: 0.00092108 [add_forward_monad_depend]: 1.104e-05 [auto_monad_grad]: 2.62001e-06 [auto_monad_eliminator]: 2.077e-05 [cse]: 5.339e-05 [replace_applicator]: 1.607e-05 [Cycle 2]: 0.00047237, [27] [switch_simplify]: 9.07001e-06 [loop_unroll]: 7.88001e-06 [a_1]: 0.00016014 [with_stream_mark]: 1.327e-05 [recompute_prepare]: 8.40999e-06 [updatestate_depend_eliminate]: 5.18002e-06 [updatestate_assign_eliminate]: 4.39998e-06 [updatestate_loads_eliminate]: 6.88e-06 [parameter_eliminate]: 1.09e-06 [specialize_transform]: 8.76002e-06 [updatestate_useless_node_eliminater]: 1.057e-05 [accelerated_algorithm]: 7.75998e-06 [meta_shard_fg_expand]: 1.81e-06 [get_grad_eliminate_]: 7.33e-06 [merge_forward]: 4.34002e-06 [cell_reuse_recompute_pass]: 1.30999e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.744e-05 [j_node_and_user_rematch]: 1.298e-05 [meta_fg_expand]: 2.63003e-06 [replace_old_param]: 1.032e-05 [inline_without_move]: 7.33999e-06 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 1.08001e-06 [auto_monad_grad]: 1.17e-06 [auto_monad_eliminator]: 9.44e-06 [cse]: 2.245e-05 [replace_applicator]: 8.13999e-06 [py_interpret_to_execute_after_opt_a]: 1.352e-05 [rewriter_after_opt_a]: 0.00028761 [convert_after_rewriter]: 1.359e-05 [order_py_execute_after_rewriter]: 8.17e-06 [mutable_eliminate]: 0.00061629 [jit_opt_b]: 7.112e-05, [1] [Cycle 1]: 6.355e-05, [2] [frontend_op_eliminate]: 2.554e-05 [inline_after_opt_a]: 2.424e-05 [cconv]: 2.906e-05 [loop_unroll]: 0.00043872 [jit_opt_after_cconv]: 0.0002183, [1] [Cycle 1]: 0.00021171, [11] [c_1]: 4.443e-05 [parameter_eliminate]: 2.07999e-06 [updatestate_depend_eliminate]: 8.59e-06 [updatestate_assign_eliminate]: 2.516e-05 [updatestate_loads_eliminate]: 4.58001e-06 [cse]: 2.845e-05 [call_graph_tuple_transform]: 2.285e-05 [tuple_list_get_item_eliminator]: 8.77999e-06 [none_parameter_eliminate]: 2.02001e-06 [renormalize]: 2.3999e-07 [switch_simplify]: 8.25999e-06 [remove_dup_value]: 2.172e-05 [partial_unused_args_eliminate]: 2.27999e-06 [environ_conv]: 2.855e-05 [add_recomputation]: 7.758e-05 [cse_after_recomputation]: 3.296e-05, [1] [Cycle 1]: 2.654e-05, [1] [cse]: 1.984e-05 [auto_monad_reorder]: 3.269e-05 [get_jit_bprop_graph]: 2.02999e-06 [rewriter_after_jit_bprop_graph]: 0.0001197 [opt_after_jit_grad]: 0.00048154 [symbol_engine_optimizer]: 0.00010351, [1] [Cycle 1]: 9.657e-05, [6] [build]: 1.363e-05 [elim_shapecalc]: 1.191e-05 [elim_not_effective]: 1.9e-05 [opt_reshape]: 8.67e-06 [fold_const_symbol]: 1.34e-05 [renormalize]: 8.2e-07 [validate]: 7.207e-05 Sums bootstrap : 0.000665s : 0.47% type_inference : 0.135867s : 96.06% event_method : 0.000018s : 0.01% auto_monad : 0.000165s : 0.12% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000011s : 0.01% py_interpret_to_execute : 0.000089s : 0.06% rewriter_before_opt_a : 0.000069s : 0.05% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000067s : 0.05% jit_opt_a.loop_unroll : 0.000029s : 0.02% jit_opt_a.a_1 : 0.000547s : 0.39% jit_opt_a.with_stream_mark : 0.000038s : 0.03% jit_opt_a.recompute_prepare : 0.000018s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000013s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000013s : 0.01% jit_opt_a.updatestate_loads_eliminate : 0.000012s : 0.01% jit_opt_a.parameter_eliminate : 0.000003s : 0.00% jit_opt_a.specialize_transform : 0.000017s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000022s : 0.02% jit_opt_a.accelerated_algorithm : 0.000016s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000016s : 0.01% jit_opt_a.merge_forward : 0.000010s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000040s : 0.03% jit_opt_a.j_node_and_user_rematch : 0.000026s : 0.02% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000023s : 0.02% jit_opt_a.inline_without_move : 0.000015s : 0.01% jit_opt_a.renormalize : 0.000921s : 0.65% jit_opt_a.add_forward_monad_depend : 0.000012s : 0.01% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000030s : 0.02% jit_opt_a.cse : 0.000076s : 0.05% jit_opt_a.replace_applicator : 0.000024s : 0.02% py_interpret_to_execute_after_opt_a : 0.000014s : 0.01% rewriter_after_opt_a : 0.000288s : 0.20% convert_after_rewriter : 0.000014s : 0.01% order_py_execute_after_rewriter : 0.000008s : 0.01% mutable_eliminate : 0.000616s : 0.44% jit_opt_b.frontend_op_eliminate : 0.000026s : 0.02% jit_opt_b.inline_after_opt_a : 0.000024s : 0.02% cconv : 0.000029s : 0.02% loop_unroll : 0.000439s : 0.31% jit_opt_after_cconv.c_1 : 0.000044s : 0.03% jit_opt_after_cconv.parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000009s : 0.01% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000025s : 0.02% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000028s : 0.02% jit_opt_after_cconv.call_graph_tuple_transform : 0.000023s : 0.02% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000009s : 0.01% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000008s : 0.01% remove_dup_value : 0.000022s : 0.02% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000029s : 0.02% add_recomputation : 0.000078s : 0.05% cse_after_recomputation.cse : 0.000020s : 0.01% auto_monad_reorder : 0.000033s : 0.02% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000120s : 0.08% opt_after_jit_grad : 0.000482s : 0.34% symbol_engine_optimizer.build : 0.000014s : 0.01% symbol_engine_optimizer.elim_shapecalc : 0.000012s : 0.01% symbol_engine_optimizer.elim_not_effective : 0.000019s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.01% symbol_engine_optimizer.fold_const_symbol : 0.000013s : 0.01% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000072s : 0.05% Time group info: ------[substitution.] 0.000177 43 4.86% : 0.000009s : 2: substitution.depend_value_elim 1.63% : 0.000003s : 4: substitution.elim_not_effective 1.19% : 0.000002s : 4: substitution.fold_const_symbol 3.74% : 0.000007s : 5: substitution.graph_param_transform 68.44% : 0.000121s : 2: substitution.inline 2.70% : 0.000005s : 8: substitution.j_node_and_user_rematch 4.36% : 0.000008s : 8: substitution.remove_not_recompute_node 3.01% : 0.000005s : 2: substitution.replace_old_param 4.60% : 0.000008s : 3: substitution.updatestate_pure_node_eliminater 5.47% : 0.000010s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.135787 2 99.28% : 0.134809s : 1: type_inference.infer 0.72% : 0.000978s : 1: type_inference.specialize ------[replace.] 0.000027 2 100.00% : 0.000027s : 2: replace.inline ------[match.] 0.000120 2 100.00% : 0.000120s : 2: match.inline ------[predicate.] 0.000134 767 1.17% : 0.000002s : 11: predicate.accumulaten_eliminater 1.52% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.48% : 0.000002s : 11: predicate.addn_check_dump 1.21% : 0.000002s : 11: predicate.addn_zero_filter 2.04% : 0.000003s : 11: predicate.arithmetic_simplify 1.14% : 0.000002s : 11: predicate.cast_eliminate 0.88% : 0.000001s : 5: predicate.check_bprop_eliminate 1.04% : 0.000001s : 11: predicate.compare_switch_simplify 1.42% : 0.000002s : 11: predicate.depend_value_elim 1.06% : 0.000001s : 11: predicate.dict_get_item_const_eliminator 1.22% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.19% : 0.000002s : 11: predicate.dict_set_item_eliminator 0.99% : 0.000001s : 5: predicate.dumpgradient_eliminate 0.58% : 0.000001s : 5: predicate.elim_not_effective 0.78% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.11% : 0.000001s : 11: predicate.environ_add_const_eliminate 1.04% : 0.000001s : 11: predicate.environ_get_add_eliminate 1.04% : 0.000001s : 11: predicate.environ_get_depend_swap 1.15% : 0.000002s : 11: predicate.environ_get_eliminate 1.07% : 0.000001s : 11: predicate.environ_get_set_eliminate 0.34% : 0.000000s : 5: predicate.fold_const_symbol 1.34% : 0.000002s : 10: predicate.get_grad_eliminate 0.45% : 0.000001s : 5: predicate.graph_param_transform 5.85% : 0.000008s : 23: predicate.inline 1.42% : 0.000002s : 10: predicate.inline_without_move 0.59% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.60% : 0.000002s : 10: predicate.less_batch_normalization 1.16% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.99% : 0.000003s : 16: predicate.load_eliminater 1.62% : 0.000002s : 5: predicate.loop_unroll_after_grad 2.99% : 0.000004s : 20: predicate.loop_unroll_before_grad 2.20% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 1.13% : 0.000002s : 11: predicate.merge_addn 1.00% : 0.000001s : 11: predicate.minmaximum_grad 1.85% : 0.000002s : 5: predicate.mutable_eliminate 0.62% : 0.000001s : 5: predicate.opt_reshape 2.24% : 0.000003s : 16: predicate.partial_eliminate 1.51% : 0.000002s : 11: predicate.print_const_string_wrapper 1.63% : 0.000002s : 11: predicate.reduce_eliminate 1.10% : 0.000001s : 11: predicate.redundant_stop_gradient_eliminater 0.99% : 0.000001s : 10: predicate.remove_not_recompute_node 1.74% : 0.000002s : 21: predicate.replace_applicator 0.93% : 0.000001s : 10: predicate.replace_old_param 0.44% : 0.000001s : 5: predicate.reset_defer_inline 1.22% : 0.000002s : 11: predicate.reshape_eliminate 1.23% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 1.32% : 0.000002s : 5: predicate.row_tensor_eliminate 1.11% : 0.000001s : 11: predicate.same_eliminate 0.73% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.47% : 0.000002s : 10: predicate.special_op_eliminate 1.37% : 0.000002s : 10: predicate.specialize_transform 1.30% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.11% : 0.000001s : 11: predicate.stack_unstack_eliminate 0.72% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.70% : 0.000002s : 13: predicate.switch_defer_inline 1.35% : 0.000002s : 13: predicate.switch_layer_defer_inline 5.85% : 0.000008s : 38: predicate.switch_simplify 1.25% : 0.000002s : 11: predicate.tile_eliminate 1.10% : 0.000001s : 11: predicate.transpose_eliminate 1.32% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.21% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.68% : 0.000005s : 21: predicate.tuple_list_get_item_eliminator 1.45% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.32% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.76% : 0.000002s : 16: predicate.updatestate_pure_node_eliminater 3.40% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.70% : 0.000002s : 11: predicate.value_based_eliminate 0.53% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.96% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000431 6 33.56% : 0.000145s : 2: func_graph_cloner_run.FuncGraphClonerGraph 66.44% : 0.000286s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.174415 72 0.05% : 0.000081s : 1: add_recomputation 0.10% : 0.000169s : 1: auto_monad 0.02% : 0.000035s : 1: auto_monad_reorder 0.39% : 0.000684s : 1: bootstrap 0.02% : 0.000032s : 1: cconv 0.01% : 0.000017s : 1: convert_after_rewriter 0.02% : 0.000035s : 1: cse_after_recomputation 0.02% : 0.000031s : 1: environ_conv 0.01% : 0.000023s : 1: event_method 0.00% : 0.000005s : 1: expand_dump_flag 0.00% : 0.000004s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 18.82% : 0.032826s : 1: jit_opt_a 0.13% : 0.000221s : 1: jit_opt_after_cconv 0.04% : 0.000074s : 1: jit_opt_b 0.26% : 0.000445s : 1: loop_unroll 0.36% : 0.000624s : 1: mutable_eliminate 0.47% : 0.000820s : 26: opt.transform.jit_opt_a 0.05% : 0.000080s : 4: opt.transform.jit_opt_after_cconv 0.02% : 0.000043s : 4: opt.transform.jit_opt_b 0.01% : 0.000016s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000019s : 1: opt.transform.mutable_eliminate 0.02% : 0.000030s : 1: opt.transform.opt_after_jit_grad 0.03% : 0.000049s : 4: opt.transform.symbol_engine_opt 0.28% : 0.000489s : 1: opt_after_jit_grad 0.01% : 0.000011s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.01% : 0.000014s : 1: pre_auto_parallel 0.05% : 0.000092s : 1: py_interpret_to_execute 0.01% : 0.000016s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000024s : 1: remove_dup_value 0.33% : 0.000570s : 1: renormalize.infer 0.20% : 0.000342s : 1: renormalize.specialize 0.07% : 0.000123s : 1: rewriter_after_jit_bprop_graph 0.17% : 0.000292s : 1: rewriter_after_opt_a 0.04% : 0.000073s : 1: rewriter_before_opt_a 0.06% : 0.000106s : 1: symbol_engine_optimizer 77.91% : 0.135885s : 1: type_inference TotalTime = 0.301907, [30] [bootstrap]: 0.00060924 [type_inference]: 0.139296 [event_method]: 0.00020704 [auto_monad]: 0.00030036 [graph_reusing]: 1.055e-05 [pre_auto_parallel]: 3.65998e-06 [py_interpret_to_execute]: 5.507e-05 [rewriter_before_opt_a]: 0.00015796 [expand_dump_flag]: 4.48001e-06 [jit_opt_a]: 0.158189, [3] [Cycle 1]: 0.149828, [27] [switch_simplify]: 0.00021341 [loop_unroll]: 6.221e-05 [a_1]: 0.00169755 [with_stream_mark]: 4.273e-05 [recompute_prepare]: 3.19e-05 [updatestate_depend_eliminate]: 3.932e-05 [updatestate_assign_eliminate]: 1.108e-05 [updatestate_loads_eliminate]: 1.048e-05 [parameter_eliminate]: 3.3e-06 [specialize_transform]: 2.237e-05 [updatestate_useless_node_eliminater]: 2.455e-05 [accelerated_algorithm]: 1.997e-05 [meta_shard_fg_expand]: 5.02e-06 [get_grad_eliminate_]: 1.886e-05 [merge_forward]: 1.23e-05 [cell_reuse_recompute_pass]: 1.07e-06 [cell_reuse_handle_not_recompute_node_pass]: 5.963e-05 [j_node_and_user_rematch]: 3.916e-05 [meta_fg_expand]: 0.0678121 [replace_old_param]: 0.00016544 [inline_without_move]: 0.00014651 [renormalize]: 0.0783166 [add_forward_monad_depend]: 2.786e-05 [auto_monad_grad]: 1.176e-05 [auto_monad_eliminator]: 9.994e-05 [cse]: 0.0003767 [replace_applicator]: 0.00023515 [Cycle 2]: 0.00401877, [27] [switch_simplify]: 7.434e-05 [loop_unroll]: 7.175e-05 [a_1]: 0.00138237 [with_stream_mark]: 3.165e-05 [recompute_prepare]: 1.652e-05 [updatestate_depend_eliminate]: 3.664e-05 [updatestate_assign_eliminate]: 6.30002e-06 [updatestate_loads_eliminate]: 5.00001e-06 [parameter_eliminate]: 2.66999e-06 [specialize_transform]: 1.068e-05 [updatestate_useless_node_eliminater]: 1.497e-05 [accelerated_algorithm]: 9.36e-06 [meta_shard_fg_expand]: 2.53e-06 [get_grad_eliminate_]: 9.07001e-06 [merge_forward]: 5.74999e-06 [cell_reuse_recompute_pass]: 1.50999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.178e-05 [j_node_and_user_rematch]: 1.537e-05 [meta_fg_expand]: 0.00014267 [replace_old_param]: 1.865e-05 [inline_without_move]: 8.62e-06 [renormalize]: 0.00177104 [add_forward_monad_depend]: 9.92999e-06 [auto_monad_grad]: 3.2e-06 [auto_monad_eliminator]: 2.457e-05 [cse]: 9.976e-05 [replace_applicator]: 2.412e-05 [Cycle 3]: 0.00054863, [27] [switch_simplify]: 9.74e-06 [loop_unroll]: 8.17e-06 [a_1]: 0.00017466 [with_stream_mark]: 1.857e-05 [recompute_prepare]: 8.44998e-06 [updatestate_depend_eliminate]: 7.38e-06 [updatestate_assign_eliminate]: 4.89003e-06 [updatestate_loads_eliminate]: 4.50999e-06 [parameter_eliminate]: 1.73002e-06 [specialize_transform]: 8.06001e-06 [updatestate_useless_node_eliminater]: 1.164e-05 [accelerated_algorithm]: 8.73001e-06 [meta_shard_fg_expand]: 2.21998e-06 [get_grad_eliminate_]: 7.85e-06 [merge_forward]: 5.95002e-06 [cell_reuse_recompute_pass]: 2.40997e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.938e-05 [j_node_and_user_rematch]: 1.382e-05 [meta_fg_expand]: 3.16001e-06 [replace_old_param]: 1.171e-05 [inline_without_move]: 7.95998e-06 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.04e-06 [auto_monad_grad]: 1.98002e-06 [auto_monad_eliminator]: 1.187e-05 [cse]: 4.831e-05 [replace_applicator]: 1.012e-05 [py_interpret_to_execute_after_opt_a]: 1.85e-05 [rewriter_after_opt_a]: 0.00020916 [convert_after_rewriter]: 1.193e-05 [order_py_execute_after_rewriter]: 6.81001e-06 [mutable_eliminate]: 0.00081816 [jit_opt_b]: 7.761e-05, [1] [Cycle 1]: 6.711e-05, [2] [frontend_op_eliminate]: 2.542e-05 [inline_after_opt_a]: 2.67e-05 [cconv]: 3.933e-05 [loop_unroll]: 0.00050077 [jit_opt_after_cconv]: 0.00024189, [1] [Cycle 1]: 0.00023391, [11] [c_1]: 5.547e-05 [parameter_eliminate]: 4.82e-06 [updatestate_depend_eliminate]: 1.25e-05 [updatestate_assign_eliminate]: 5.45001e-06 [updatestate_loads_eliminate]: 4.80001e-06 [cse]: 4.622e-05 [call_graph_tuple_transform]: 2.55e-05 [tuple_list_get_item_eliminator]: 9.16002e-06 [none_parameter_eliminate]: 1.81e-06 [renormalize]: 3.09985e-07 [switch_simplify]: 9.02999e-06 [remove_dup_value]: 2.854e-05 [partial_unused_args_eliminate]: 2.46e-06 [environ_conv]: 1.187e-05 [add_recomputation]: 7.686e-05 [cse_after_recomputation]: 4.008e-05, [1] [Cycle 1]: 3.29e-05, [1] [cse]: 2.445e-05 [auto_monad_reorder]: 2.959e-05 [get_jit_bprop_graph]: 2.49999e-06 [rewriter_after_jit_bprop_graph]: 6.61e-06 [opt_after_jit_grad]: 0.00055425 [symbol_engine_optimizer]: 0.00011054, [1] [Cycle 1]: 0.00010248, [6] [build]: 1.403e-05 [elim_shapecalc]: 1.285e-05 [elim_not_effective]: 2.196e-05 [opt_reshape]: 8.82e-06 [fold_const_symbol]: 1.38e-05 [renormalize]: 6.09987e-07 [validate]: 5.619e-05 Sums bootstrap : 0.000609s : 0.21% type_inference : 0.139296s : 46.89% event_method : 0.000207s : 0.07% auto_monad : 0.000300s : 0.10% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000055s : 0.02% rewriter_before_opt_a : 0.000158s : 0.05% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000297s : 0.10% jit_opt_a.loop_unroll : 0.000142s : 0.05% jit_opt_a.a_1 : 0.003255s : 1.10% jit_opt_a.with_stream_mark : 0.000093s : 0.03% jit_opt_a.recompute_prepare : 0.000057s : 0.02% jit_opt_a.updatestate_depend_eliminate : 0.000083s : 0.03% jit_opt_a.updatestate_assign_eliminate : 0.000022s : 0.01% jit_opt_a.updatestate_loads_eliminate : 0.000020s : 0.01% jit_opt_a.parameter_eliminate : 0.000008s : 0.00% jit_opt_a.specialize_transform : 0.000041s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000051s : 0.02% jit_opt_a.accelerated_algorithm : 0.000038s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000010s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000036s : 0.01% jit_opt_a.merge_forward : 0.000024s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000101s : 0.03% jit_opt_a.j_node_and_user_rematch : 0.000068s : 0.02% jit_opt_a.meta_fg_expand : 0.067958s : 22.87% jit_opt_a.replace_old_param : 0.000196s : 0.07% jit_opt_a.inline_without_move : 0.000163s : 0.05% jit_opt_a.renormalize : 0.080088s : 26.96% jit_opt_a.add_forward_monad_depend : 0.000040s : 0.01% jit_opt_a.auto_monad_grad : 0.000017s : 0.01% jit_opt_a.auto_monad_eliminator : 0.000136s : 0.05% jit_opt_a.cse : 0.000525s : 0.18% jit_opt_a.replace_applicator : 0.000269s : 0.09% py_interpret_to_execute_after_opt_a : 0.000018s : 0.01% rewriter_after_opt_a : 0.000209s : 0.07% convert_after_rewriter : 0.000012s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000818s : 0.28% jit_opt_b.frontend_op_eliminate : 0.000025s : 0.01% jit_opt_b.inline_after_opt_a : 0.000027s : 0.01% cconv : 0.000039s : 0.01% loop_unroll : 0.000501s : 0.17% jit_opt_after_cconv.c_1 : 0.000055s : 0.02% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000013s : 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 : 0.000046s : 0.02% jit_opt_after_cconv.call_graph_tuple_transform : 0.000025s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000009s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000009s : 0.00% remove_dup_value : 0.000029s : 0.01% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000012s : 0.00% add_recomputation : 0.000077s : 0.03% cse_after_recomputation.cse : 0.000024s : 0.01% auto_monad_reorder : 0.000030s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000554s : 0.19% symbol_engine_optimizer.build : 0.000014s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000022s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000056s : 0.02% Time group info: ------[substitution.] 0.002491 217 1.23% : 0.000031s : 11: substitution.depend_value_elim 0.12% : 0.000003s : 4: substitution.elim_not_effective 0.08% : 0.000002s : 4: substitution.fold_const_symbol 59.37% : 0.001479s : 9: substitution.getattr_setattr_resolve 0.28% : 0.000007s : 5: substitution.graph_param_transform 23.06% : 0.000575s : 17: substitution.inline 1.71% : 0.000043s : 5: substitution.inline_without_move 0.55% : 0.000014s : 21: substitution.j_node_and_user_rematch 0.81% : 0.000020s : 10: substitution.minmaximum_grad 0.31% : 0.000008s : 9: substitution.partial_eliminate 0.63% : 0.000016s : 21: substitution.remove_not_recompute_node 2.18% : 0.000054s : 15: substitution.replace_applicator 0.74% : 0.000018s : 19: substitution.replace_old_param 0.14% : 0.000004s : 1: substitution.set_cell_output_no_recompute 0.64% : 0.000016s : 3: substitution.switch_simplify 1.95% : 0.000049s : 10: substitution.tuple_list_convert_item_index_to_positive 1.60% : 0.000040s : 11: substitution.tuple_list_get_item_depend_reorder 2.02% : 0.000050s : 15: substitution.tuple_list_get_item_eliminator 0.94% : 0.000023s : 11: substitution.updatestate_pure_node_eliminater 1.64% : 0.000041s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.139170 2 97.74% : 0.136022s : 1: type_inference.infer 2.26% : 0.003148s : 1: type_inference.specialize ------[replace.] 0.000546 34 26.04% : 0.000142s : 7: replace.getattr_setattr_resolve 26.46% : 0.000145s : 17: replace.inline 10.04% : 0.000055s : 1: replace.replace_applicator 11.77% : 0.000064s : 3: replace.switch_simplify 2.09% : 0.000011s : 1: replace.tuple_list_get_item_depend_reorder 19.16% : 0.000105s : 4: replace.tuple_list_get_item_eliminator 4.44% : 0.000024s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002000 34 68.52% : 0.001370s : 7: match.getattr_setattr_resolve 28.18% : 0.000564s : 17: match.inline 0.71% : 0.000014s : 1: match.replace_applicator 0.69% : 0.000014s : 3: match.switch_simplify 0.69% : 0.000014s : 1: match.tuple_list_get_item_depend_reorder 0.50% : 0.000010s : 4: match.tuple_list_get_item_eliminator 0.70% : 0.000014s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000596 3867 1.44% : 0.000009s : 62: predicate.accumulaten_eliminater 0.39% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.36% : 0.000008s : 62: predicate.addn_check_dump 1.39% : 0.000008s : 62: predicate.addn_zero_filter 1.77% : 0.000011s : 62: predicate.arithmetic_simplify 1.46% : 0.000009s : 62: predicate.cast_eliminate 0.15% : 0.000001s : 5: predicate.check_bprop_eliminate 1.34% : 0.000008s : 62: predicate.compare_switch_simplify 1.59% : 0.000009s : 62: predicate.depend_value_elim 1.33% : 0.000008s : 62: predicate.dict_get_item_const_eliminator 1.37% : 0.000008s : 62: predicate.dict_get_item_eliminator 1.38% : 0.000008s : 62: predicate.dict_set_item_eliminator 0.39% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.14% : 0.000001s : 5: predicate.elim_not_effective 0.26% : 0.000002s : 5: predicate.elim_shapecalc_of_broadcastargs 1.40% : 0.000008s : 62: predicate.environ_add_const_eliminate 1.36% : 0.000008s : 62: predicate.environ_get_add_eliminate 1.34% : 0.000008s : 62: predicate.environ_get_depend_swap 1.50% : 0.000009s : 62: predicate.environ_get_eliminate 1.36% : 0.000008s : 62: predicate.environ_get_set_eliminate 0.07% : 0.000000s : 5: predicate.fold_const_symbol 0.82% : 0.000005s : 27: predicate.get_grad_eliminate 2.50% : 0.000015s : 51: predicate.getattr_setattr_resolve 0.11% : 0.000001s : 5: predicate.graph_param_transform 4.18% : 0.000025s : 95: predicate.inline 3.20% : 0.000019s : 110: predicate.inline_without_move 0.33% : 0.000002s : 27: predicate.j_node_and_user_rematch 1.03% : 0.000006s : 27: predicate.less_batch_normalization 1.55% : 0.000009s : 67: predicate.list_to_tuple_eliminator_ 1.65% : 0.000010s : 72: predicate.load_eliminater 0.69% : 0.000004s : 5: predicate.loop_unroll_after_grad 3.66% : 0.000022s : 151: predicate.loop_unroll_before_grad 1.70% : 0.000010s : 68: predicate.make_slice_get_slice_eliminator 1.40% : 0.000008s : 62: predicate.merge_addn 1.40% : 0.000008s : 62: predicate.minmaximum_grad 0.81% : 0.000005s : 5: predicate.mutable_eliminate 0.15% : 0.000001s : 5: predicate.opt_reshape 2.14% : 0.000013s : 72: predicate.partial_eliminate 1.36% : 0.000008s : 62: predicate.print_const_string_wrapper 1.81% : 0.000011s : 62: predicate.reduce_eliminate 1.60% : 0.000010s : 67: predicate.redundant_stop_gradient_eliminater 0.48% : 0.000003s : 27: predicate.remove_not_recompute_node 2.72% : 0.000016s : 157: predicate.replace_applicator 1.48% : 0.000009s : 110: predicate.replace_old_param 0.18% : 0.000001s : 5: predicate.reset_defer_inline 1.40% : 0.000008s : 62: predicate.reshape_eliminate 1.46% : 0.000009s : 62: predicate.row_tensor_add_zeros_like 0.27% : 0.000002s : 5: predicate.row_tensor_eliminate 1.46% : 0.000009s : 62: predicate.same_eliminate 0.46% : 0.000003s : 32: predicate.set_cell_output_no_recompute 0.31% : 0.000002s : 10: predicate.special_op_eliminate 0.80% : 0.000005s : 27: predicate.specialize_transform 1.60% : 0.000010s : 62: predicate.split_environ_get_set_with_tuple_value 1.42% : 0.000008s : 62: predicate.stack_unstack_eliminate 0.18% : 0.000001s : 5: predicate.switch_call_monad_eliminater 2.63% : 0.000016s : 85: predicate.switch_defer_inline 2.22% : 0.000013s : 85: predicate.switch_layer_defer_inline 6.59% : 0.000039s : 247: predicate.switch_simplify 1.52% : 0.000009s : 62: predicate.tile_eliminate 1.39% : 0.000008s : 62: predicate.transpose_eliminate 1.77% : 0.000011s : 62: predicate.tuple_list_convert_item_index_to_positive 1.68% : 0.000010s : 63: predicate.tuple_list_get_item_depend_reorder 3.02% : 0.000018s : 77: predicate.tuple_list_get_item_eliminator 1.90% : 0.000011s : 63: predicate.tuple_list_set_item_eliminator 1.50% : 0.000009s : 67: predicate.tuple_to_list_eliminator_ 1.70% : 0.000010s : 72: predicate.updatestate_pure_node_eliminater 2.77% : 0.000017s : 100: predicate.updatestate_useless_node_eliminater 1.84% : 0.000011s : 62: predicate.value_based_eliminate 0.15% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.22% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.005147 61 69.31% : 0.003567s : 31: func_graph_cloner_run.FuncGraphClonerGraph 30.69% : 0.001580s : 30: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.388525 91 0.02% : 0.000080s : 1: add_recomputation 0.08% : 0.000308s : 1: auto_monad 0.01% : 0.000033s : 1: auto_monad_reorder 0.16% : 0.000637s : 1: bootstrap 0.01% : 0.000042s : 1: cconv 0.00% : 0.000015s : 1: convert_after_rewriter 0.01% : 0.000042s : 1: cse_after_recomputation 0.00% : 0.000014s : 1: environ_conv 0.06% : 0.000218s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 40.72% : 0.158194s : 1: jit_opt_a 0.06% : 0.000245s : 1: jit_opt_after_cconv 0.02% : 0.000081s : 1: jit_opt_b 0.13% : 0.000508s : 1: loop_unroll 0.21% : 0.000827s : 1: mutable_eliminate 1.20% : 0.004648s : 39: opt.transform.jit_opt_a 0.02% : 0.000094s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000044s : 4: opt.transform.jit_opt_b 0.01% : 0.000023s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000027s : 1: opt.transform.mutable_eliminate 0.01% : 0.000037s : 1: opt.transform.opt_after_jit_grad 0.45% : 0.001758s : 4: opt.transform.opt_resolve 0.01% : 0.000054s : 4: opt.transform.symbol_engine_opt 0.14% : 0.000562s : 1: opt_after_jit_grad 0.00% : 0.000009s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.02% : 0.000059s : 1: py_interpret_to_execute 0.01% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000032s : 1: remove_dup_value 19.48% : 0.075671s : 2: renormalize.infer 1.13% : 0.004391s : 2: renormalize.specialize 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.000213s : 1: rewriter_after_opt_a 0.04% : 0.000162s : 1: rewriter_before_opt_a 0.03% : 0.000114s : 1: symbol_engine_optimizer 35.86% : 0.139318s : 1: type_inference . [hook] pytest_runtest_teardown:test_chunk_single_chunk[KBK] tests/st/mint/test_chunk.py::test_chunk_single_chunk[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 103.83s (0:01:43) ==================