RN启动报错[Workarounds] Packager unable to resolve module from /Users/node_modules/

最新推荐文章于 2023-05-18 13:15:37 发布
原创 最新推荐文章于 2023-05-18 13:15:37 发布 · 689 阅读 · 0 ·
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博客围绕React Native中无法解析`AccessibilityInfo`模块的问题展开。给出了相关GitHub链接，列举了通用解决办法，如清除watchman watches、删除`node_modules`等。作者自身情况是安装运行正常，引入`react-navigation`未使用，次日运行报错，注释引入后问题解决。

github：https://github.com/facebook/react-native/issues/4968

也在说这问题

Unable to resolve module `AccessibilityInfo` from `xxx\node_modules\react-native\Libraries\
react-native\react-native-implementation.js`: Module does not exist in the module map This might be related to https://github.com/facebook/react-native/issues/4968 To resolve try the following: 1. Clear watchman watches: `watchman watch-del-all`. 2. Delete the `node_modules` folder: `rm -rf node_modules && npm install`. 3. Reset Metro Bundler cache: `rm -rf $TMPDIR/react-*` or `npm start -- --reset-cache`. 4. Remove haste cache: `rm -rf $TMPDIR/haste-map-react-native-packager-*`.

 

我的情况是这样的，安装运行没有问题然后开始写代码，第二天打开，报错看提示说要删node_modules等等操作

我个人推测的原因：

我把react-navigation引入了没有使用第二天过来运行报错

解决方法

把引入注释掉就可以了

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- 报错`Descriptors cannot be created directly`表明存在Protobuf版本冲突 - 某些库（如TensorFlow或PyTorch扩展）需要Protobuf 3.19+生成的代码，但当前环境可能安装了旧版本[^2] --- #### **分步解决方案** ...
Traceback (most recent call last): File "/home/xianbei/CNN-VehicleType/test_vehicle_type.py", line 17, in <module> from keras.preprocessing.image import img_to_array File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/keras/__init__.py", line 3, in <module> from keras import __internal__ File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/keras/__internal__/__init__.py", line 3, in <module> from keras.__internal__ import backend File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/keras/__internal__/backend/__init__.py", line 3, in <module> from keras.src.backend import _initialize_variables as initialize_variables File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/keras/src/__init__.py", line 21, in <module> from keras.src import applications File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/keras/src/applications/__init__.py", line 18, in <module> from keras.src.applications.convnext import ConvNeXtBase File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/keras/src/applications/convnext.py", line 26, in <module> import tensorflow.compat.v2 as tf File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/tensorflow/__init__.py", line 41, in <module> from tensorflow.python.tools import module_util as _module_util File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/tensorflow/python/__init__.py", line 53, in <module> from tensorflow.core.framework.graph_pb2 import * File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/tensorflow/core/framework/graph_pb2.py", line 16, in <module> from tensorflow.core.framework import function_pb2 as tensorflow_dot_core_dot_framework_dot_function__pb2 File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/tensorflow/core/framework/function_pb2.py", line 16, in <module> from tensorflow.core.framework import attr_value_pb2 as tensorflow_dot_core_dot_framework_dot_attr__value__pb2 File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/tensorflow/core/framework/attr_value_pb2.py", line 16, in <module> from tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2 File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/tensorflow/core/framework/tensor_pb2.py", line 16, in <module> from tensorflow.core.framework import resource_handle_pb2 as tensorflow_dot_core_dot_framework_dot_resource__handle__pb2 File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/tensorflow/core/framework/resource_handle_pb2.py", line 16, in <module> from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2 File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/tensorflow/core/framework/tensor_shape_pb2.py", line 36, in <module> _descriptor.FieldDescriptor( File "/home/xianbei/anaconda3/envs/py38/lib/python3.8/site-packages/google/protobuf/descriptor.py", line 621, in __new__ _message.Message._CheckCalledFromGeneratedFile() TypeError: Descriptors cannot be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are: 1. Downgrade the protobuf package to 3.20.x or lower. 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).
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--------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-35-b42d4f2a0683> in <module> 1 import pandas as pd 2 import numpy as np ----> 3 import tensorflow as tf 4 5 # 1. 加载CSV文件（针对指定路径） /usr/local/lib/python3.7/site-packages/tensorflow/__init__.py in <module> 22 23 # pylint: disable=g-bad-import-order ---> 24 from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import 25 26 from tensorflow._api.v1 import app /usr/local/lib/python3.7/site-packages/tensorflow/python/__init__.py in <module> 50 51 # Protocol buffers ---> 52 from tensorflow.core.framework.graph_pb2 import * 53 from tensorflow.core.framework.node_def_pb2 import * 54 from tensorflow.core.framework.summary_pb2 import * /usr/local/lib/python3.7/site-packages/tensorflow/core/framework/graph_pb2.py in <module> 13 14 ---> 15 from tensorflow.core.framework import node_def_pb2 as tensorflow_dot_core_dot_framework_dot_node__def__pb2 16 from tensorflow.core.framework import function_pb2 as tensorflow_dot_core_dot_framework_dot_function__pb2 17 from tensorflow.core.framework import versions_pb2 as tensorflow_dot_core_dot_framework_dot_versions__pb2 /usr/local/lib/python3.7/site-packages/tensorflow/core/framework/node_def_pb2.py in <module> 13 14 ---> 15 from tensorflow.core.framework import attr_value_pb2 as tensorflow_dot_core_dot_framework_dot_attr__value__pb2 16 17 /usr/local/lib/python3.7/site-packages/tensorflow/core/framework/attr_value_pb2.py in <module> 13 14 ---> 15 from tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2 16 from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2 17 from tensorflow.core.framework import types_pb2 as tensorflow_dot_core_dot_framework_dot_types__pb2 /usr/local/lib/python3.7/site-packages/tensorflow/core/framework/tensor_pb2.py in <module> 13 14 ---> 15 from tensorflow.core.framework import resource_handle_pb2 as tensorflow_dot_core_dot_framework_dot_resource__handle__pb2 16 from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2 17 from tensorflow.core.framework import types_pb2 as tensorflow_dot_core_dot_framework_dot_types__pb2 /usr/local/lib/python3.7/site-packages/tensorflow/core/framework/resource_handle_pb2.py in <module> 39 message_type=None, enum_type=None, containing_type=None, 40 is_extension=False, extension_scope=None, ---> 41 serialized_options=None, file=DESCRIPTOR), 42 _descriptor.FieldDescriptor( 43 name='container', full_name='tensorflow.ResourceHandleProto.container', index=1, /usr/local/lib/python3.7/site-packages/google/protobuf/descriptor.py in __new__(cls, name, full_name, index, number, type, cpp_type, label, default_value, message_type, enum_type, containing_type, is_extension, extension_scope, options, serialized_options, has_default_value, containing_oneof, json_name, file, create_key) 559 has_default_value=True, containing_oneof=None, json_name=None, 560 file=None, create_key=None): # pylint: disable=redefined-builtin --> 561 _message.Message._CheckCalledFromGeneratedFile() 562 if is_extension: 563 return _message.default_pool.FindExtensionByName(full_name) TypeError: Descriptors cannot not be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are: 1. Downgrade the protobuf package to 3.20.x or lower. 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower). More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates
06-09
# If this call came from a _pb2.py file... # 步骤2：解决protobuf冲突（关键步骤） pip uninstall -y protobuf tensorflow # 卸载冲突组件 pip install protobuf==3.20.3 # 安装兼容版本[^1] pip install --...
(egpo_fix) (base) dwh@dwh:~/EGPO$ /home/dwh/anaconda3/envs/egpo_fix/bin/python /home/dwh/EGPO/training_script/train_cql.py Traceback (most recent call last): File "/home/dwh/EGPO/training_script/train_cql.py", line 3, in <module> import ray File "/home/dwh/anaconda3/envs/egpo_fix/lib/python3.7/site-packages/ray/__init__.py", line 63, in <module> import ray._raylet # noqa: E402 File "python/ray/_raylet.pyx", line 102, in init ray._raylet File "/home/dwh/anaconda3/envs/egpo_fix/lib/python3.7/site-packages/ray/exceptions.py", line 7, in <module> from ray.core.generated.common_pb2 import RayException, Language, PYTHON File "/home/dwh/anaconda3/envs/egpo_fix/lib/python3.7/site-packages/ray/core/generated/common_pb2.py", line 36, in <module> type=None), File "/home/dwh/anaconda3/envs/egpo_fix/lib/python3.7/site-packages/google/protobuf/descriptor.py", line 796, in __new__ _message.Message._CheckCalledFromGeneratedFile() TypeError: Descriptors cannot not be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are: 1. Downgrade the protobuf package to 3.20.x or lower. 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower). More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates
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若仍报错，尝试在全新虚拟环境中重新安装依赖： ```bash conda create -n ray_fix python=3.8 conda activate ray_fix pip install "protobuf ``` --- **注意**：若依赖其他库（如 `tensorflow`），需确保其与 `...
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This error message usually occurs ...Alternatively, you can check the documentation or support forums for the software package to see if there are any known issues or workarounds for this error message.
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