Description
During LightGBM model training, an exception occurs when creating cache directories, caused by invalid path syntax with non-UTF8 characters.
Error Message:boost::filesystem::create_directories: The filename, directory name, or volume label syntax is incorrect. [system:123]: "C:\Users\l\AppData\Roaming\boost_compute\0\x91\0I0???"
Interpreted Error Context:
The original GBK-encoded error message \xce\xc4\xbc\xfe\xc3\xfb\xa1\xa2\xc4\xbf\xc2\xbc\xc3\xfb\xbb\xf2\xbe\xed\xb1\xea\xd3\xef\xb7\xa8\xb2\xbb\xd5\xfd\xc8\xb7\xa1\xa3 translates to:
"The filename, directory name, or volume label syntax is incorrect."
Reproducible example
import lightgbm as lgb
params = {
'objective': 'binary',
'num_iterations': 100,
'verbose': 1
}
Sample data
import numpy as np
X = np.random.rand(1000, 10)
y = np.random.randint(2, size=1000)
train_data = lgb.Dataset(X, label=y)
Trigger error
lgb.train(params, train_data) # Fails during cache directory creation
Expected Behavior
LightGBM should automatically create cache directories with valid pathnames and complete training successfully.
Environment info
OS: Windows 11
LightGBM Version: lightgbm-4.6.0-cpu_py_1 from conda-forge
Python Version: 3.12.9
LightGBM version or commit hash:
Command(s) you used to install LightGBM
conda install lightgbm
Additional Comments
when pip install lightgbm,then it works very good
Description
During LightGBM model training, an exception occurs when creating cache directories, caused by invalid path syntax with non-UTF8 characters.
Error Message:boost::filesystem::create_directories: The filename, directory name, or volume label syntax is incorrect. [system:123]: "C:\Users\l\AppData\Roaming\boost_compute\0\x91\0I0???"
Interpreted Error Context:
The original GBK-encoded error message \xce\xc4\xbc\xfe\xc3\xfb\xa1\xa2\xc4\xbf\xc2\xbc\xc3\xfb\xbb\xf2\xbe\xed\xb1\xea\xd3\xef\xb7\xa8\xb2\xbb\xd5\xfd\xc8\xb7\xa1\xa3 translates to:
"The filename, directory name, or volume label syntax is incorrect."
Reproducible example
import lightgbm as lgb
params = {
'objective': 'binary',
'num_iterations': 100,
'verbose': 1
}
Sample data
import numpy as np
X = np.random.rand(1000, 10)
y = np.random.randint(2, size=1000)
train_data = lgb.Dataset(X, label=y)
Trigger error
lgb.train(params, train_data) # Fails during cache directory creation
Expected Behavior
LightGBM should automatically create cache directories with valid pathnames and complete training successfully.
Environment info
LightGBM version or commit hash:
Command(s) you used to install LightGBM
conda install lightgbm
Additional Comments
when pip install lightgbm,then it works very good