/usr/lib/python2.6 和 /usr/lib64/python 的区别

本文解释了Python库在不同文件夹中的安装位置选择依据。架构独立的库应安装在/usr/lib/python2.6下,而架构相关的库则应放置于/usr/lib64/python2.6。无论库位于何处,Python在导入时都会同时搜索这两个路径。

摘自老外的解释http://lists.fedoraproject.org/pipermail/users/2009-August/087219.html


It seems i have two python2.6 folders located in /usr/lib vs

/usr/lib64  respectively.  Most python stuff (source) is in
/usr/lib64/python2.6 but when in installed packages they have been
put into /usr/lib/python2.6

Architecture-dependent python modules go in /usr/lib64/python*, while

architecture-independent modules go in /usr/lib/python*.  Python's

module path checks both for modules when importing.


总的意思就是:

如果你的库是架构独立的,那么就放到/usr/lib/python2.6 下

如果你的库不是架构独立的,那么放到/usr/lib64/python2.6下


放心好了,当你import时

python会连这2个路径一起搜索的

(most recent call last): File "run_VisionTextCLS.py", line 707, in <module> history = model.fit( File "/usr/local/conda/envs/vitst/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1105, in fit callbacks.on_train_batch_end(end_step, logs) File "/usr/local/conda/envs/vitst/lib/python3.8/site-packages/tensorflow/python/keras/callbacks.py", line 454, in on_train_batch_end self._call_batch_hook(ModeKeys.TRAIN, 'end', batch, logs=logs) File "/usr/local/conda/envs/vitst/lib/python3.8/site-packages/tensorflow/python/keras/callbacks.py", line 296, in _call_batch_hook self._call_batch_end_hook(mode, batch, logs) File "/usr/local/conda/envs/vitst/lib/python3.8/site-packages/tensorflow/python/keras/callbacks.py", line 316, in _call_batch_end_hook self._call_batch_hook_helper(hook_name, batch, logs) File "/usr/local/conda/envs/vitst/lib/python3.8/site-packages/tensorflow/python/keras/callbacks.py", line 360, in _call_batch_hook_helper hook(batch, numpy_logs) File "run_VisionTextCLS.py", line 102, in on_train_batch_end results = self.model.evaluate(self.val_dataset, verbose=0) File "/usr/local/conda/envs/vitst/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1384, in evaluate self.reset_metrics() File "/usr/local/conda/envs/vitst/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1669, in reset_metrics m.reset_states() File "/usr/local/conda/envs/vitst/lib/python3.8/site-packages/tensorflow/python/keras/metrics.py", line 253, in reset_states K.batch_set_value([(v, 0) for v in self.variables]) File "/usr/local/conda/envs/vitst/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py", line 201, in wrapper return target(*args, **kwargs) File "/usr/local/conda/envs/vitst/lib/python3.8/site-packages/tensorflow/python/keras/backend.py", line 3706, in batch_set_value x.assign(np.asarray(value, dtype=dtype(x))) File "/usr/local/conda/envs/vitst/lib/python3.8/site-packages/tensorflow/python/ops/resource_variable_ops.py", line 888, in assign raise ValueError( ValueError: Cannot assign to variable true_positives:0 due to variable shape (1,) and value shape () are incompatible出现上面问题的原因是什么
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