==================================================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_004/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_chunk.py . [hook] pytest_runtest_teardown:test_chunk_negative_dim[pynative] tests/st/mint/test_chunk.py::test_chunk_negative_dim[pynative],max_mem:2.0M TotalTime = 0.722517, [30] [bootstrap]: 0.00063237 [type_inference]: 0.563671 [event_method]: 1.696e-05 [auto_monad]: 0.00020607 [graph_reusing]: 7.49002e-06 [pre_auto_parallel]: 1.277e-05 [py_interpret_to_execute]: 0.00013577 [rewriter_before_opt_a]: 7.202e-05 [expand_dump_flag]: 3.65e-06 [jit_opt_a]: 0.154403, [2] [Cycle 1]: 0.146878, [27] [switch_simplify]: 6.387e-05 [loop_unroll]: 1.914e-05 [a_1]: 0.00045363 [with_stream_mark]: 2.861e-05 [recompute_prepare]: 1.009e-05 [updatestate_depend_eliminate]: 7.65e-06 [updatestate_assign_eliminate]: 9.62999e-06 [updatestate_loads_eliminate]: 5.10001e-06 [parameter_eliminate]: 1.86003e-06 [specialize_transform]: 9.27001e-06 [updatestate_useless_node_eliminater]: 1.107e-05 [accelerated_algorithm]: 9.79999e-06 [meta_shard_fg_expand]: 3.31001e-06 [get_grad_eliminate_]: 8.55999e-06 [merge_forward]: 5.23002e-06 [cell_reuse_recompute_pass]: 1.36002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.364e-05 [j_node_and_user_rematch]: 1.379e-05 [meta_fg_expand]: 4.08001e-06 [replace_old_param]: 1.291e-05 [inline_without_move]: 8.13999e-06 [renormalize]: 0.145771 [add_forward_monad_depend]: 1.86e-05 [auto_monad_grad]: 2.89999e-06 [auto_monad_eliminator]: 3.174e-05 [cse]: 4.937e-05 [replace_applicator]: 3.438e-05 [Cycle 2]: 0.00053556, [27] [switch_simplify]: 1.051e-05 [loop_unroll]: 8.54998e-06 [a_1]: 0.00019062 [with_stream_mark]: 1.974e-05 [recompute_prepare]: 8.3e-06 [updatestate_depend_eliminate]: 6.83998e-06 [updatestate_assign_eliminate]: 5.82999e-06 [updatestate_loads_eliminate]: 4.39002e-06 [parameter_eliminate]: 2.27999e-06 [specialize_transform]: 1.237e-05 [updatestate_useless_node_eliminater]: 1.11e-05 [accelerated_algorithm]: 8.36002e-06 [meta_shard_fg_expand]: 3.24001e-06 [get_grad_eliminate_]: 8e-06 [merge_forward]: 6.01e-06 [cell_reuse_recompute_pass]: 2.99001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.964e-05 [j_node_and_user_rematch]: 1.271e-05 [meta_fg_expand]: 3.96001e-06 [replace_old_param]: 1.159e-05 [inline_without_move]: 7.95998e-06 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 1.80001e-06 [auto_monad_grad]: 9.00007e-07 [auto_monad_eliminator]: 1.065e-05 [cse]: 2.297e-05 [replace_applicator]: 7.95e-06 [py_interpret_to_execute_after_opt_a]: 1.958e-05 [rewriter_after_opt_a]: 0.00033549 [convert_after_rewriter]: 1.532e-05 [order_py_execute_after_rewriter]: 7.93999e-06 [mutable_eliminate]: 0.00084982 [jit_opt_b]: 7.576e-05, [1] [Cycle 1]: 6.56e-05, [2] [frontend_op_eliminate]: 2.692e-05 [inline_after_opt_a]: 2.406e-05 [cconv]: 3.688e-05 [loop_unroll]: 0.00046478 [jit_opt_after_cconv]: 0.00021209, [1] [Cycle 1]: 0.00020432, [11] [c_1]: 4.787e-05 [parameter_eliminate]: 4.27998e-06 [updatestate_depend_eliminate]: 1.03e-05 [updatestate_assign_eliminate]: 5.60001e-06 [updatestate_loads_eliminate]: 4.10998e-06 [cse]: 3.424e-05 [call_graph_tuple_transform]: 2.336e-05 [tuple_list_get_item_eliminator]: 8.32e-06 [none_parameter_eliminate]: 1.88002e-06 [renormalize]: 2.69996e-07 [switch_simplify]: 8.79e-06 [remove_dup_value]: 2.383e-05 [partial_unused_args_eliminate]: 2.23998e-06 [environ_conv]: 0.00012334 [add_recomputation]: 8.436e-05 [cse_after_recomputation]: 3.257e-05, [1] [Cycle 1]: 2.553e-05, [1] [cse]: 1.892e-05 [auto_monad_reorder]: 3.689e-05 [get_jit_bprop_graph]: 2.45002e-06 [rewriter_after_jit_bprop_graph]: 4.72e-06 [opt_after_jit_grad]: 0.00049776 [symbol_engine_optimizer]: 0.00011045, [1] [Cycle 1]: 0.00010264, [6] [build]: 1.704e-05 [elim_shapecalc]: 1.256e-05 [elim_not_effective]: 1.924e-05 [opt_reshape]: 9.11002e-06 [fold_const_symbol]: 1.394e-05 [renormalize]: 2.60014e-07 [validate]: 8.417e-05 Sums bootstrap : 0.000632s : 0.09% type_inference : 0.563671s : 78.87% event_method : 0.000017s : 0.00% auto_monad : 0.000206s : 0.03% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000013s : 0.00% py_interpret_to_execute : 0.000136s : 0.02% rewriter_before_opt_a : 0.000072s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000074s : 0.01% jit_opt_a.loop_unroll : 0.000028s : 0.00% jit_opt_a.a_1 : 0.000644s : 0.09% jit_opt_a.with_stream_mark : 0.000048s : 0.01% jit_opt_a.recompute_prepare : 0.000018s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000022s : 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 : 0.000007s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000017s : 0.00% jit_opt_a.merge_forward : 0.000011s : 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 : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000026s : 0.00% jit_opt_a.meta_fg_expand : 0.000008s : 0.00% jit_opt_a.replace_old_param : 0.000024s : 0.00% jit_opt_a.inline_without_move : 0.000016s : 0.00% jit_opt_a.renormalize : 0.145771s : 20.40% jit_opt_a.add_forward_monad_depend : 0.000020s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000042s : 0.01% jit_opt_a.cse : 0.000072s : 0.01% jit_opt_a.replace_applicator : 0.000042s : 0.01% py_interpret_to_execute_after_opt_a : 0.000020s : 0.00% rewriter_after_opt_a : 0.000335s : 0.05% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000850s : 0.12% jit_opt_b.frontend_op_eliminate : 0.000027s : 0.00% jit_opt_b.inline_after_opt_a : 0.000024s : 0.00% cconv : 0.000037s : 0.01% loop_unroll : 0.000465s : 0.07% jit_opt_after_cconv.c_1 : 0.000048s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000034s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000023s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000008s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000009s : 0.00% remove_dup_value : 0.000024s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000123s : 0.02% add_recomputation : 0.000084s : 0.01% cse_after_recomputation.cse : 0.000019s : 0.00% auto_monad_reorder : 0.000037s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.000498s : 0.07% symbol_engine_optimizer.build : 0.000017s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000019s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000084s : 0.01% Time group info: ------[substitution.] 0.000239 43 5.20% : 0.000012s : 2: substitution.depend_value_elim 1.28% : 0.000003s : 4: substitution.elim_not_effective 1.08% : 0.000003s : 4: substitution.fold_const_symbol 3.30% : 0.000008s : 5: substitution.graph_param_transform 71.95% : 0.000172s : 2: substitution.inline 2.01% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.45% : 0.000008s : 8: substitution.remove_not_recompute_node 2.77% : 0.000007s : 2: substitution.replace_old_param 4.89% : 0.000012s : 3: substitution.updatestate_pure_node_eliminater 4.09% : 0.000010s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.563564 2 99.74% : 0.562092s : 1: type_inference.infer 0.26% : 0.001473s : 1: type_inference.specialize ------[replace.] 0.000032 2 100.00% : 0.000032s : 2: replace.inline ------[match.] 0.000170 2 100.00% : 0.000170s : 2: match.inline ------[predicate.] 0.000147 767 1.29% : 0.000002s : 11: predicate.accumulaten_eliminater 1.41% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.15% : 0.000002s : 11: predicate.addn_check_dump 1.19% : 0.000002s : 11: predicate.addn_zero_filter 2.13% : 0.000003s : 11: predicate.arithmetic_simplify 1.30% : 0.000002s : 11: predicate.cast_eliminate 0.54% : 0.000001s : 5: predicate.check_bprop_eliminate 1.09% : 0.000002s : 11: predicate.compare_switch_simplify 1.27% : 0.000002s : 11: predicate.depend_value_elim 1.02% : 0.000001s : 11: predicate.dict_get_item_const_eliminator 1.26% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.41% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.13% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.35% : 0.000001s : 5: predicate.elim_not_effective 0.90% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.42% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.11% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.08% : 0.000002s : 11: predicate.environ_get_depend_swap 1.24% : 0.000002s : 11: predicate.environ_get_eliminate 1.07% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.31% : 0.000000s : 5: predicate.fold_const_symbol 1.52% : 0.000002s : 10: predicate.get_grad_eliminate 0.31% : 0.000000s : 5: predicate.graph_param_transform 4.81% : 0.000007s : 23: predicate.inline 1.12% : 0.000002s : 10: predicate.inline_without_move 0.50% : 0.000001s : 10: predicate.j_node_and_user_rematch 2.36% : 0.000003s : 10: predicate.less_batch_normalization 1.49% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.79% : 0.000003s : 16: predicate.load_eliminater 1.53% : 0.000002s : 5: predicate.loop_unroll_after_grad 2.23% : 0.000003s : 20: predicate.loop_unroll_before_grad 1.91% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 1.14% : 0.000002s : 11: predicate.merge_addn 1.11% : 0.000002s : 11: predicate.minmaximum_grad 2.90% : 0.000004s : 5: predicate.mutable_eliminate 0.71% : 0.000001s : 5: predicate.opt_reshape 2.05% : 0.000003s : 16: predicate.partial_eliminate 1.16% : 0.000002s : 11: predicate.print_const_string_wrapper 1.93% : 0.000003s : 11: predicate.reduce_eliminate 1.41% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.92% : 0.000001s : 10: predicate.remove_not_recompute_node 1.85% : 0.000003s : 21: predicate.replace_applicator 0.98% : 0.000001s : 10: predicate.replace_old_param 0.37% : 0.000001s : 5: predicate.reset_defer_inline 1.23% : 0.000002s : 11: predicate.reshape_eliminate 1.22% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 1.36% : 0.000002s : 5: predicate.row_tensor_eliminate 1.21% : 0.000002s : 11: predicate.same_eliminate 0.69% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.33% : 0.000002s : 10: predicate.special_op_eliminate 1.38% : 0.000002s : 10: predicate.specialize_transform 1.20% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.17% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.58% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.47% : 0.000002s : 13: predicate.switch_defer_inline 1.42% : 0.000002s : 13: predicate.switch_layer_defer_inline 6.14% : 0.000009s : 38: predicate.switch_simplify 1.10% : 0.000002s : 11: predicate.tile_eliminate 1.32% : 0.000002s : 11: predicate.transpose_eliminate 1.48% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.56% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 4.20% : 0.000006s : 21: predicate.tuple_list_get_item_eliminator 1.49% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.19% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.62% : 0.000002s : 16: predicate.updatestate_pure_node_eliminater 3.32% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.39% : 0.000002s : 11: predicate.value_based_eliminate 0.43% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.77% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000673 6 23.59% : 0.000159s : 2: func_graph_cloner_run.FuncGraphClonerGraph 76.41% : 0.000514s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.869218 72 0.01% : 0.000088s : 1: add_recomputation 0.02% : 0.000212s : 1: auto_monad 0.00% : 0.000040s : 1: auto_monad_reorder 0.08% : 0.000661s : 1: bootstrap 0.00% : 0.000040s : 1: cconv 0.00% : 0.000018s : 1: convert_after_rewriter 0.00% : 0.000035s : 1: cse_after_recomputation 0.01% : 0.000127s : 1: environ_conv 0.00% : 0.000022s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 17.76% : 0.154407s : 1: jit_opt_a 0.02% : 0.000215s : 1: jit_opt_after_cconv 0.01% : 0.000079s : 1: jit_opt_b 0.05% : 0.000474s : 1: loop_unroll 0.10% : 0.000863s : 1: mutable_eliminate 0.11% : 0.000948s : 26: opt.transform.jit_opt_a 0.01% : 0.000084s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000044s : 4: opt.transform.jit_opt_b 0.00% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000025s : 1: opt.transform.mutable_eliminate 0.00% : 0.000031s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000051s : 4: opt.transform.symbol_engine_opt 0.06% : 0.000507s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000016s : 1: pre_auto_parallel 0.02% : 0.000139s : 1: py_interpret_to_execute 0.00% : 0.000022s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000026s : 1: remove_dup_value 16.69% : 0.145103s : 1: renormalize.infer 0.08% : 0.000653s : 1: renormalize.specialize 0.00% : 0.000007s : 1: rewriter_after_jit_bprop_graph 0.04% : 0.000340s : 1: rewriter_after_opt_a 0.01% : 0.000076s : 1: rewriter_before_opt_a 0.01% : 0.000113s : 1: symbol_engine_optimizer 64.85% : 0.563699s : 1: type_inference TotalTime = 0.450574, [30] [bootstrap]: 0.00053764 [type_inference]: 0.43672 [event_method]: 1.989e-05 [auto_monad]: 0.0001645 [graph_reusing]: 6.91999e-06 [pre_auto_parallel]: 2.93998e-06 [py_interpret_to_execute]: 0.00016985 [rewriter_before_opt_a]: 6.375e-05 [expand_dump_flag]: 3.45998e-06 [jit_opt_a]: 0.00930567, [2] [Cycle 1]: 0.00287126, [27] [switch_simplify]: 6.745e-05 [loop_unroll]: 2.109e-05 [a_1]: 0.00053677 [with_stream_mark]: 3.56e-05 [recompute_prepare]: 1.319e-05 [updatestate_depend_eliminate]: 8.23999e-06 [updatestate_assign_eliminate]: 5.79e-06 [updatestate_loads_eliminate]: 5.17e-06 [parameter_eliminate]: 2.63003e-06 [specialize_transform]: 1.139e-05 [updatestate_useless_node_eliminater]: 1.482e-05 [accelerated_algorithm]: 1.175e-05 [meta_shard_fg_expand]: 4.73001e-06 [get_grad_eliminate_]: 1.029e-05 [merge_forward]: 6.59001e-06 [cell_reuse_recompute_pass]: 2.01003e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.513e-05 [j_node_and_user_rematch]: 1.615e-05 [meta_fg_expand]: 4.3e-06 [replace_old_param]: 1.58e-05 [inline_without_move]: 1.03e-05 [renormalize]: 0.00163916 [add_forward_monad_depend]: 1.781e-05 [auto_monad_grad]: 3.00998e-06 [auto_monad_eliminator]: 3.186e-05 [cse]: 5.265e-05 [replace_applicator]: 2.957e-05 [Cycle 2]: 0.00155984, [27] [switch_simplify]: 1.122e-05 [loop_unroll]: 9.52999e-06 [a_1]: 0.00021722 [with_stream_mark]: 2.151e-05 [recompute_prepare]: 2.307e-05 [updatestate_depend_eliminate]: 9.81e-06 [updatestate_assign_eliminate]: 6.77002e-06 [updatestate_loads_eliminate]: 6.49001e-06 [parameter_eliminate]: 1.87999e-06 [specialize_transform]: 1.071e-05 [updatestate_useless_node_eliminater]: 1.275e-05 [accelerated_algorithm]: 1.036e-05 [meta_shard_fg_expand]: 3.01999e-06 [get_grad_eliminate_]: 0.00012244 [merge_forward]: 1.682e-05 [cell_reuse_recompute_pass]: 4.2e-06 [cell_reuse_handle_not_recompute_node_pass]: 8.233e-05 [j_node_and_user_rematch]: 2.155e-05 [meta_fg_expand]: 2.497e-05 [replace_old_param]: 2.018e-05 [inline_without_move]: 1.116e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 6.36e-06 [auto_monad_grad]: 3.26999e-06 [auto_monad_eliminator]: 2.615e-05 [cse]: 4.952e-05 [replace_applicator]: 1.236e-05 [py_interpret_to_execute_after_opt_a]: 2.783e-05 [rewriter_after_opt_a]: 0.00033829 [convert_after_rewriter]: 1.462e-05 [order_py_execute_after_rewriter]: 7.90998e-06 [mutable_eliminate]: 0.00089372 [jit_opt_b]: 8.91e-05, [1] [Cycle 1]: 7.893e-05, [2] [frontend_op_eliminate]: 3.16e-05 [inline_after_opt_a]: 3.093e-05 [cconv]: 4.408e-05 [loop_unroll]: 0.00056867 [jit_opt_after_cconv]: 0.00025826, [1] [Cycle 1]: 0.00025007, [11] [c_1]: 5.883e-05 [parameter_eliminate]: 4.99e-06 [updatestate_depend_eliminate]: 1.451e-05 [updatestate_assign_eliminate]: 6.38e-06 [updatestate_loads_eliminate]: 5.58002e-06 [cse]: 4.777e-05 [call_graph_tuple_transform]: 2.707e-05 [tuple_list_get_item_eliminator]: 9.54999e-06 [none_parameter_eliminate]: 2.08002e-06 [renormalize]: 4.30009e-07 [switch_simplify]: 9.94001e-06 [remove_dup_value]: 2.639e-05 [partial_unused_args_eliminate]: 3.15002e-06 [environ_conv]: 1.462e-05 [add_recomputation]: 8.464e-05 [cse_after_recomputation]: 3.852e-05, [1] [Cycle 1]: 3.055e-05, [1] [cse]: 2.24e-05 [auto_monad_reorder]: 3.087e-05 [get_jit_bprop_graph]: 2.44001e-06 [rewriter_after_jit_bprop_graph]: 9.53002e-06 [opt_after_jit_grad]: 0.00065628 [symbol_engine_optimizer]: 0.00012866, [1] [Cycle 1]: 0.00011934, [6] [build]: 1.808e-05 [elim_shapecalc]: 1.618e-05 [elim_not_effective]: 2.357e-05 [opt_reshape]: 9.97999e-06 [fold_const_symbol]: 1.571e-05 [renormalize]: 6.59988e-07 [validate]: 7.02e-05 Sums bootstrap : 0.000538s : 0.12% type_inference : 0.436720s : 98.32% event_method : 0.000020s : 0.00% auto_monad : 0.000165s : 0.04% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000003s : 0.00% py_interpret_to_execute : 0.000170s : 0.04% rewriter_before_opt_a : 0.000064s : 0.01% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000079s : 0.02% jit_opt_a.loop_unroll : 0.000031s : 0.01% jit_opt_a.a_1 : 0.000754s : 0.17% jit_opt_a.with_stream_mark : 0.000057s : 0.01% jit_opt_a.recompute_prepare : 0.000036s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000018s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000012s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000022s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000028s : 0.01% jit_opt_a.accelerated_algorithm : 0.000022s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000008s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000133s : 0.03% jit_opt_a.merge_forward : 0.000023s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000107s : 0.02% jit_opt_a.j_node_and_user_rematch : 0.000038s : 0.01% jit_opt_a.meta_fg_expand : 0.000029s : 0.01% jit_opt_a.replace_old_param : 0.000036s : 0.01% jit_opt_a.inline_without_move : 0.000021s : 0.00% jit_opt_a.renormalize : 0.001639s : 0.37% jit_opt_a.add_forward_monad_depend : 0.000024s : 0.01% jit_opt_a.auto_monad_grad : 0.000006s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000058s : 0.01% jit_opt_a.cse : 0.000102s : 0.02% jit_opt_a.replace_applicator : 0.000042s : 0.01% py_interpret_to_execute_after_opt_a : 0.000028s : 0.01% rewriter_after_opt_a : 0.000338s : 0.08% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000894s : 0.20% jit_opt_b.frontend_op_eliminate : 0.000032s : 0.01% jit_opt_b.inline_after_opt_a : 0.000031s : 0.01% cconv : 0.000044s : 0.01% loop_unroll : 0.000569s : 0.13% jit_opt_after_cconv.c_1 : 0.000059s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 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 : 0.000048s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000027s : 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 : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000010s : 0.00% remove_dup_value : 0.000026s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000015s : 0.00% add_recomputation : 0.000085s : 0.02% cse_after_recomputation.cse : 0.000022s : 0.01% auto_monad_reorder : 0.000031s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.000656s : 0.15% symbol_engine_optimizer.build : 0.000018s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000016s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000024s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000016s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000070s : 0.02% Time group info: ------[substitution.] 0.000324 43 3.44% : 0.000011s : 2: substitution.depend_value_elim 1.05% : 0.000003s : 4: substitution.elim_not_effective 0.76% : 0.000002s : 4: substitution.fold_const_symbol 2.48% : 0.000008s : 5: substitution.graph_param_transform 61.93% : 0.000201s : 2: substitution.inline 2.50% : 0.000008s : 8: substitution.j_node_and_user_rematch 16.24% : 0.000053s : 8: substitution.remove_not_recompute_node 2.97% : 0.000010s : 2: substitution.replace_old_param 4.02% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 4.60% : 0.000015s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.436630 2 99.67% : 0.435197s : 1: type_inference.infer 0.33% : 0.001433s : 1: type_inference.specialize ------[replace.] 0.000037 2 100.00% : 0.000037s : 2: replace.inline ------[match.] 0.000198 2 100.00% : 0.000198s : 2: match.inline ------[predicate.] 0.000179 767 1.18% : 0.000002s : 11: predicate.accumulaten_eliminater 1.52% : 0.000003s : 5: predicate.ad_related_special_op_eliminate 0.91% : 0.000002s : 11: predicate.addn_check_dump 1.31% : 0.000002s : 11: predicate.addn_zero_filter 2.19% : 0.000004s : 11: predicate.arithmetic_simplify 1.48% : 0.000003s : 11: predicate.cast_eliminate 0.65% : 0.000001s : 5: predicate.check_bprop_eliminate 1.05% : 0.000002s : 11: predicate.compare_switch_simplify 1.54% : 0.000003s : 11: predicate.depend_value_elim 1.12% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.28% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.18% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.20% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.46% : 0.000001s : 5: predicate.elim_not_effective 0.80% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.14% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.09% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.05% : 0.000002s : 11: predicate.environ_get_depend_swap 1.14% : 0.000002s : 11: predicate.environ_get_eliminate 1.06% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.25% : 0.000000s : 5: predicate.fold_const_symbol 3.18% : 0.000006s : 10: predicate.get_grad_eliminate 0.23% : 0.000000s : 5: predicate.graph_param_transform 4.45% : 0.000008s : 23: predicate.inline 1.48% : 0.000003s : 10: predicate.inline_without_move 0.70% : 0.000001s : 10: predicate.j_node_and_user_rematch 2.46% : 0.000004s : 10: predicate.less_batch_normalization 1.33% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.75% : 0.000003s : 16: predicate.load_eliminater 2.06% : 0.000004s : 5: predicate.loop_unroll_after_grad 2.13% : 0.000004s : 20: predicate.loop_unroll_before_grad 1.75% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 1.15% : 0.000002s : 11: predicate.merge_addn 1.12% : 0.000002s : 11: predicate.minmaximum_grad 2.74% : 0.000005s : 5: predicate.mutable_eliminate 0.78% : 0.000001s : 5: predicate.opt_reshape 1.90% : 0.000003s : 16: predicate.partial_eliminate 1.35% : 0.000002s : 11: predicate.print_const_string_wrapper 1.54% : 0.000003s : 11: predicate.reduce_eliminate 1.24% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.92% : 0.000002s : 10: predicate.remove_not_recompute_node 1.53% : 0.000003s : 21: predicate.replace_applicator 0.78% : 0.000001s : 10: predicate.replace_old_param 0.69% : 0.000001s : 5: predicate.reset_defer_inline 1.14% : 0.000002s : 11: predicate.reshape_eliminate 1.16% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.96% : 0.000002s : 5: predicate.row_tensor_eliminate 1.35% : 0.000002s : 11: predicate.same_eliminate 0.61% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.21% : 0.000002s : 10: predicate.special_op_eliminate 1.09% : 0.000002s : 10: predicate.specialize_transform 1.56% : 0.000003s : 11: predicate.split_environ_get_set_with_tuple_value 1.21% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.54% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.95% : 0.000003s : 13: predicate.switch_defer_inline 1.53% : 0.000003s : 13: predicate.switch_layer_defer_inline 5.73% : 0.000010s : 38: predicate.switch_simplify 1.11% : 0.000002s : 11: predicate.tile_eliminate 1.39% : 0.000002s : 11: predicate.transpose_eliminate 1.51% : 0.000003s : 11: predicate.tuple_list_convert_item_index_to_positive 1.19% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.82% : 0.000007s : 21: predicate.tuple_list_get_item_eliminator 1.42% : 0.000003s : 11: predicate.tuple_list_set_item_eliminator 1.16% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.58% : 0.000003s : 16: predicate.updatestate_pure_node_eliminater 3.21% : 0.000006s : 26: predicate.updatestate_useless_node_eliminater 1.68% : 0.000003s : 11: predicate.value_based_eliminate 0.45% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.58% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000579 6 25.50% : 0.000148s : 2: func_graph_cloner_run.FuncGraphClonerGraph 74.50% : 0.000432s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.453640 72 0.02% : 0.000088s : 1: add_recomputation 0.04% : 0.000171s : 1: auto_monad 0.01% : 0.000035s : 1: auto_monad_reorder 0.12% : 0.000565s : 1: bootstrap 0.01% : 0.000047s : 1: cconv 0.00% : 0.000018s : 1: convert_after_rewriter 0.01% : 0.000042s : 1: cse_after_recomputation 0.00% : 0.000017s : 1: environ_conv 0.01% : 0.000026s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 2.05% : 0.009312s : 1: jit_opt_a 0.06% : 0.000263s : 1: jit_opt_after_cconv 0.02% : 0.000093s : 1: jit_opt_b 0.13% : 0.000581s : 1: loop_unroll 0.20% : 0.000909s : 1: mutable_eliminate 0.28% : 0.001291s : 26: opt.transform.jit_opt_a 0.02% : 0.000100s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000052s : 4: opt.transform.jit_opt_b 0.01% : 0.000023s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000030s : 1: opt.transform.mutable_eliminate 0.01% : 0.000039s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000061s : 4: opt.transform.symbol_engine_opt 0.15% : 0.000669s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.04% : 0.000174s : 1: py_interpret_to_execute 0.01% : 0.000031s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000030s : 1: remove_dup_value 0.23% : 0.001043s : 1: renormalize.infer 0.13% : 0.000581s : 1: renormalize.specialize 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.08% : 0.000345s : 1: rewriter_after_opt_a 0.02% : 0.000068s : 1: rewriter_before_opt_a 0.03% : 0.000132s : 1: symbol_engine_optimizer 96.28% : 0.436747s : 1: type_inference TotalTime = 0.362776, [30] [bootstrap]: 0.00033909 [type_inference]: 0.259967 [event_method]: 1.644e-05 [auto_monad]: 0.00014786 [graph_reusing]: 6.83e-06 [pre_auto_parallel]: 2.31e-06 [py_interpret_to_execute]: 0.00013555 [rewriter_before_opt_a]: 6.262e-05 [expand_dump_flag]: 4.06001e-06 [jit_opt_a]: 0.0990152, [2] [Cycle 1]: 0.00214627, [27] [switch_simplify]: 5.938e-05 [loop_unroll]: 1.819e-05 [a_1]: 0.00045079 [with_stream_mark]: 2.449e-05 [recompute_prepare]: 1.056e-05 [updatestate_depend_eliminate]: 6.69001e-06 [updatestate_assign_eliminate]: 5.62999e-06 [updatestate_loads_eliminate]: 4.94998e-06 [parameter_eliminate]: 1.91998e-06 [specialize_transform]: 9.17001e-06 [updatestate_useless_node_eliminater]: 1.076e-05 [accelerated_algorithm]: 8.72e-06 [meta_shard_fg_expand]: 3.13e-06 [get_grad_eliminate_]: 8.08001e-06 [merge_forward]: 6.07001e-06 [cell_reuse_recompute_pass]: 1.37999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.097e-05 [j_node_and_user_rematch]: 1.466e-05 [meta_fg_expand]: 3.45e-06 [replace_old_param]: 1.195e-05 [inline_without_move]: 8.35001e-06 [renormalize]: 0.00115226 [add_forward_monad_depend]: 7.08e-06 [auto_monad_grad]: 2.81e-06 [auto_monad_eliminator]: 2.22e-05 [cse]: 4.322e-05 [replace_applicator]: 2.054e-05 [Cycle 2]: 0.00050201, [27] [switch_simplify]: 9.91998e-06 [loop_unroll]: 8.12998e-06 [a_1]: 0.00017564 [with_stream_mark]: 1.322e-05 [recompute_prepare]: 8.41002e-06 [updatestate_depend_eliminate]: 5.62999e-06 [updatestate_assign_eliminate]: 4.45e-06 [updatestate_loads_eliminate]: 4.10998e-06 [parameter_eliminate]: 1.56998e-06 [specialize_transform]: 8.12e-06 [updatestate_useless_node_eliminater]: 1.011e-05 [accelerated_algorithm]: 7.88999e-06 [meta_shard_fg_expand]: 1.89999e-06 [get_grad_eliminate_]: 8.25999e-06 [merge_forward]: 5.10001e-06 [cell_reuse_recompute_pass]: 2.24001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.775e-05 [j_node_and_user_rematch]: 1.309e-05 [meta_fg_expand]: 2.89001e-06 [replace_old_param]: 1.107e-05 [inline_without_move]: 7.46001e-06 [renormalize]: 9.00181e-08 [add_forward_monad_depend]: 1.25001e-06 [auto_monad_grad]: 1.15001e-06 [auto_monad_eliminator]: 1.028e-05 [cse]: 2.431e-05 [replace_applicator]: 7.83001e-06 [py_interpret_to_execute_after_opt_a]: 1.579e-05 [rewriter_after_opt_a]: 0.00027869 [convert_after_rewriter]: 1.269e-05 [order_py_execute_after_rewriter]: 7.43e-06 [mutable_eliminate]: 0.00082174 [jit_opt_b]: 7.776e-05, [1] [Cycle 1]: 6.765e-05, [2] [frontend_op_eliminate]: 2.631e-05 [inline_after_opt_a]: 2.666e-05 [cconv]: 2.78e-05 [loop_unroll]: 0.0004864 [jit_opt_after_cconv]: 0.0002257, [1] [Cycle 1]: 0.00021785, [11] [c_1]: 4.907e-05 [parameter_eliminate]: 4.1e-06 [updatestate_depend_eliminate]: 1.133e-05 [updatestate_assign_eliminate]: 5.43002e-06 [updatestate_loads_eliminate]: 4.79e-06 [cse]: 3.873e-05 [call_graph_tuple_transform]: 2.503e-05 [tuple_list_get_item_eliminator]: 8.49002e-06 [none_parameter_eliminate]: 1.81998e-06 [renormalize]: 8.2e-07 [switch_simplify]: 9.29e-06 [remove_dup_value]: 2.188e-05 [partial_unused_args_eliminate]: 2.56998e-06 [environ_conv]: 1.268e-05 [add_recomputation]: 7.072e-05 [cse_after_recomputation]: 3.284e-05, [1] [Cycle 1]: 2.651e-05, [1] [cse]: 1.989e-05 [auto_monad_reorder]: 2.624e-05 [get_jit_bprop_graph]: 2.27999e-06 [rewriter_after_jit_bprop_graph]: 6.23002e-06 [opt_after_jit_grad]: 0.00054874 [symbol_engine_optimizer]: 0.00010968, [1] [Cycle 1]: 0.00010183, [6] [build]: 1.358e-05 [elim_shapecalc]: 1.322e-05 [elim_not_effective]: 1.853e-05 [opt_reshape]: 9.17999e-06 [fold_const_symbol]: 1.433e-05 [renormalize]: 1.09e-06 [validate]: 6.121e-05 Sums bootstrap : 0.000339s : 0.13% type_inference : 0.259967s : 97.84% event_method : 0.000016s : 0.01% auto_monad : 0.000148s : 0.06% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000002s : 0.00% py_interpret_to_execute : 0.000136s : 0.05% rewriter_before_opt_a : 0.000063s : 0.02% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000069s : 0.03% jit_opt_a.loop_unroll : 0.000026s : 0.01% jit_opt_a.a_1 : 0.000626s : 0.24% jit_opt_a.with_stream_mark : 0.000038s : 0.01% jit_opt_a.recompute_prepare : 0.000019s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000010s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000003s : 0.00% jit_opt_a.specialize_transform : 0.000017s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000021s : 0.01% jit_opt_a.accelerated_algorithm : 0.000017s : 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 : 0.000011s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000039s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000028s : 0.01% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000023s : 0.01% jit_opt_a.inline_without_move : 0.000016s : 0.01% jit_opt_a.renormalize : 0.001152s : 0.43% jit_opt_a.add_forward_monad_depend : 0.000008s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000032s : 0.01% jit_opt_a.cse : 0.000068s : 0.03% jit_opt_a.replace_applicator : 0.000028s : 0.01% py_interpret_to_execute_after_opt_a : 0.000016s : 0.01% rewriter_after_opt_a : 0.000279s : 0.10% convert_after_rewriter : 0.000013s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000822s : 0.31% jit_opt_b.frontend_op_eliminate : 0.000026s : 0.01% jit_opt_b.inline_after_opt_a : 0.000027s : 0.01% cconv : 0.000028s : 0.01% loop_unroll : 0.000486s : 0.18% jit_opt_after_cconv.c_1 : 0.000049s : 0.02% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000011s : 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 : 0.000039s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000025s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000008s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000009s : 0.00% remove_dup_value : 0.000022s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000013s : 0.00% add_recomputation : 0.000071s : 0.03% cse_after_recomputation.cse : 0.000020s : 0.01% auto_monad_reorder : 0.000026s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000549s : 0.21% symbol_engine_optimizer.build : 0.000014s : 0.01% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000019s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.01% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000061s : 0.02% Time group info: ------[substitution.] 0.000214 43 4.42% : 0.000009s : 2: substitution.depend_value_elim 1.36% : 0.000003s : 4: substitution.elim_not_effective 1.02% : 0.000002s : 4: substitution.fold_const_symbol 3.38% : 0.000007s : 5: substitution.graph_param_transform 71.98% : 0.000154s : 2: substitution.inline 2.17% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.68% : 0.000008s : 8: substitution.remove_not_recompute_node 2.43% : 0.000005s : 2: substitution.replace_old_param 4.89% : 0.000010s : 3: substitution.updatestate_pure_node_eliminater 4.67% : 0.000010s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.259891 2 99.53% : 0.258668s : 1: type_inference.infer 0.47% : 0.001223s : 1: type_inference.specialize ------[replace.] 0.000029 2 100.00% : 0.000029s : 2: replace.inline ------[match.] 0.000153 2 100.00% : 0.000153s : 2: match.inline ------[predicate.] 0.000149 767 1.28% : 0.000002s : 11: predicate.accumulaten_eliminater 1.47% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.22% : 0.000002s : 11: predicate.addn_check_dump 1.28% : 0.000002s : 11: predicate.addn_zero_filter 1.88% : 0.000003s : 11: predicate.arithmetic_simplify 1.55% : 0.000002s : 11: predicate.cast_eliminate 0.50% : 0.000001s : 5: predicate.check_bprop_eliminate 1.20% : 0.000002s : 11: predicate.compare_switch_simplify 1.45% : 0.000002s : 11: predicate.depend_value_elim 1.04% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.33% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.29% : 0.000002s : 11: predicate.dict_set_item_eliminator 0.89% : 0.000001s : 5: predicate.dumpgradient_eliminate 0.34% : 0.000000s : 5: predicate.elim_not_effective 0.81% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.27% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.32% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.26% : 0.000002s : 11: predicate.environ_get_depend_swap 1.34% : 0.000002s : 11: predicate.environ_get_eliminate 0.96% : 0.000001s : 11: predicate.environ_get_set_eliminate 0.30% : 0.000000s : 5: predicate.fold_const_symbol 1.18% : 0.000002s : 10: predicate.get_grad_eliminate 0.40% : 0.000001s : 5: predicate.graph_param_transform 5.23% : 0.000008s : 23: predicate.inline 1.17% : 0.000002s : 10: predicate.inline_without_move 0.50% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.44% : 0.000002s : 10: predicate.less_batch_normalization 1.41% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.81% : 0.000003s : 16: predicate.load_eliminater 1.41% : 0.000002s : 5: predicate.loop_unroll_after_grad 2.37% : 0.000004s : 20: predicate.loop_unroll_before_grad 2.33% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 1.41% : 0.000002s : 11: predicate.merge_addn 1.02% : 0.000002s : 11: predicate.minmaximum_grad 2.52% : 0.000004s : 5: predicate.mutable_eliminate 0.84% : 0.000001s : 5: predicate.opt_reshape 1.81% : 0.000003s : 16: predicate.partial_eliminate 1.26% : 0.000002s : 11: predicate.print_const_string_wrapper 2.09% : 0.000003s : 11: predicate.reduce_eliminate 1.35% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.79% : 0.000001s : 10: predicate.remove_not_recompute_node 1.61% : 0.000002s : 21: predicate.replace_applicator 0.95% : 0.000001s : 10: predicate.replace_old_param 0.61% : 0.000001s : 5: predicate.reset_defer_inline 1.26% : 0.000002s : 11: predicate.reshape_eliminate 1.29% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.91% : 0.000001s : 5: predicate.row_tensor_eliminate 1.23% : 0.000002s : 11: predicate.same_eliminate 0.67% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.14% : 0.000002s : 10: predicate.special_op_eliminate 1.28% : 0.000002s : 10: predicate.specialize_transform 1.41% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.39% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.67% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.54% : 0.000002s : 13: predicate.switch_defer_inline 1.55% : 0.000002s : 13: predicate.switch_layer_defer_inline 5.93% : 0.000009s : 38: predicate.switch_simplify 1.22% : 0.000002s : 11: predicate.tile_eliminate 1.18% : 0.000002s : 11: predicate.transpose_eliminate 1.31% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.41% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 4.26% : 0.000006s : 21: predicate.tuple_list_get_item_eliminator 1.51% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.28% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.63% : 0.000002s : 16: predicate.updatestate_pure_node_eliminater 3.47% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.64% : 0.000002s : 11: predicate.value_based_eliminate 0.48% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.83% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000450 6 30.59% : 0.000138s : 2: func_graph_cloner_run.FuncGraphClonerGraph 69.41% : 0.000312s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.364955 72 0.02% : 0.000074s : 1: add_recomputation 0.04% : 0.000153s : 1: auto_monad 0.01% : 0.000029s : 1: auto_monad_reorder 0.10% : 0.000360s : 1: bootstrap 0.01% : 0.000031s : 1: cconv 0.00% : 0.000016s : 1: convert_after_rewriter 0.01% : 0.000035s : 1: cse_after_recomputation 0.00% : 0.000015s : 1: environ_conv 0.01% : 0.000022s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 27.13% : 0.099021s : 1: jit_opt_a 0.06% : 0.000229s : 1: jit_opt_after_cconv 0.02% : 0.000081s : 1: jit_opt_b 0.14% : 0.000497s : 1: loop_unroll 0.23% : 0.000835s : 1: mutable_eliminate 0.25% : 0.000912s : 26: opt.transform.jit_opt_a 0.02% : 0.000088s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000045s : 4: opt.transform.jit_opt_b 0.00% : 0.000017s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000023s : 1: opt.transform.mutable_eliminate 0.01% : 0.000034s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000051s : 4: opt.transform.symbol_engine_opt 0.15% : 0.000559s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pre_auto_parallel 0.04% : 0.000139s : 1: py_interpret_to_execute 0.01% : 0.000019s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000025s : 1: remove_dup_value 0.20% : 0.000738s : 1: renormalize.infer 0.11% : 0.000405s : 1: renormalize.specialize 0.00% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.08% : 0.000284s : 1: rewriter_after_opt_a 0.02% : 0.000067s : 1: rewriter_before_opt_a 0.03% : 0.000112s : 1: symbol_engine_optimizer 71.24% : 0.259990s : 1: type_inference . [hook] pytest_runtest_teardown:test_chunk_negative_dim[KBK] tests/st/mint/test_chunk.py::test_chunk_negative_dim[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 100.68s (0:01:40) ==================