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[MDT][MT] [910B]deeplabv3_vocaug 执行export.py时报错

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创建于  
2024-04-10 16:30
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Describe the current behavior / 问题描述 (Mandatory / 必填)

deeplabv3_vocaug 执行export.py时报错

Environment / 环境信息 (Mandatory / 必填)

  • Hardware Environment(Ascend/GPU/CPU) / 硬件环境:

Please delete the backend not involved / 请删除不涉及的后端:
/device ascend

  • Software Environment / 软件环境 (Mandatory / 必填):
    -- MindSpore version (e.g., 1.7.0.Bxxx) :2.3.0rc1+20240409 commit_id = '[sha1]:4d2fc036,[branch]:(HEAD,origin/r2.3.q1,r2.3.q1)'
    -- Python version (e.g., Python 3.7.5) :Python 3.7.6
    -- OS platform and distribution (e.g., Linux Ubuntu 16.04):4.19.90-vhulk2211.3.0.h1543.eulerosv2r10.aarch64
    -- GCC/Compiler version (if compiled from source): gcc version 7.3.0 (GCC)
    2.3.q1 run包Milan_C17/20240406

  • Excute Mode / 执行模式 (Mandatory / 必填)(PyNative/Graph):

Please delete the mode not involved / 请删除不涉及的模式:
/mode graph

Related testcase / 关联用例 (Mandatory / 必填)

test_ms_deeplabv3_vocaug_310p_export_mindir_0001

Steps to reproduce the issue / 重现步骤 (Mandatory / 必填)

1.get code from solution_test
2.cd solution_test/cases/02network/00cv/deeplabv3/export/
3.pytest -s test_ms_deeplabv3_vocaug_310p_export_mindir_0001.py
4.验证执行export.py时正常 是否正常

Describe the expected behavior / 预期结果 (Mandatory / 必填)

deeplabv3_vocaug 执行export.py时正常

Related log / screenshot / 日志 / 截图 (Mandatory / 必填)

[INFO] ATRACE(857639,python):2024-04-10-14:03:31.759.510 tracer_schedule.c:187 destory object RUNTIME_ATRACE_DEV0_TS0, exitSave(false).
Traceback (most recent call last):
File "export.py", line 75, in
run_export()
File "/home/jenkins0/cty/solution_test/cases/02network/00cv/deeplabv3/export/test_ms_deeplabv3_vocaug_310p_export_mindir_0001/model_utils/moxing_adapter.py", line 105, in wrapped_func
run_func(*args, **kwargs)
File "export.py", line 71, in run_export
export(network, input_data, file_name=config.file_name, file_format=config.file_format)
File "/home/miniconda3/envs/ci/lib/python3.7/site-packages/mindspore/train/serialization.py", line 1783, in export
_export(net, file_name, file_format, *inputs, **kwargs)
File "/home/miniconda3/envs/ci/lib/python3.7/site-packages/mindspore/train/serialization.py", line 1841, in _export
_save_mindir(net, file_name, *inputs, **kwargs)
File "/home/miniconda3/envs/ci/lib/python3.7/site-packages/mindspore/train/serialization.py", line 2114, in _save_mindir
mindir_stream, net_dict = _cell_info(net, incremental, *inputs)
File "/home/miniconda3/envs/ci/lib/python3.7/site-packages/mindspore/train/serialization.py", line 2063, in _cell_info
graph_id, _ = _executor.compile(net, *inputs, phase=phase_name, do_convert=False)
File "/home/miniconda3/envs/ci/lib/python3.7/site-packages/mindspore/common/api.py", line 1590, in compile
result = self._graph_executor.compile(obj, args, kwargs, phase, self._use_vm_mode())
AttributeError: External object has no attribute ResizeBilinear


  • C++ Call Stack: (For framework developers)

mindspore/ccsrc/pipeline/jit/ps/static_analysis/prim.cc:1772 GetEvaluatedValueForNameSpaceString


  • The Traceback of Net Construct Code:

0 In file export.py:36

    if self.format == "NHWC":

1 In file export.py:38

    output = self.network(x)
             ^

2 In file /home/jenkins0/cty/solution_test/cases/02network/00cv/deeplabv3/export/test_ms_deeplabv3_vocaug_310p_export_mindir_0001/src/nets/deeplab_v3/deeplab_v3.py:218

    out = P.ResizeBilinear((size[2], size[3]), True)(out)
          ^

Special notes for this issue/备注 (Optional / 选填)

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请为此issue分配处理人。
@chentangyu

感谢您的提问,您可以评论//mindspore-assistant更快获取帮助:

  1. 如果您刚刚接触MindSpore,或许您可以在教程找到答案
  2. 如果您是资深Pytorch用户,您或许需要:
  1. 如果您遇到动态图问题,可以设置set_context(pynative_synchronize=True)查看报错栈协助定位
  2. 模型精度调优问题可参考官网调优指南
  3. 如果您反馈的是框架BUG,请确认您在ISSUE中提供了MindSpore版本、使用的后端类型(CPU、GPU、Ascend)、环境、训练的代码官方链接以及可以复现报错的代码的启动方式等必要的定位信息
  4. 如果您已经定位出问题根因,欢迎提交PR参与MindSpore开源社区,我们会尽快review
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“AttributeError: External object has no attribute ResizeBilinear”
算子接口ResizeBilinear在新版本MindSpore已移除,改用ResizeBilinearV2。

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在910B机器 Milan_C17/20240414 r2.3.q1_20240414031117_d8944576745840adc802e945e0c486c43a1a1dd1 环境下 回归通过
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