sklearn中报错ValueError: Expected 2D array, got 1D array instead:

from sklearn.linear_model import LinearRegression
lr = LinearRegression()
print(tr_x.shape,tr_y.shape)
lr.fit(tr_x,tr_y) # 报错
(64,) (64,)
Traceback (most recent call last):
File "F:/Python_Project/sklearn2_2/zong_fu_xi/A_02.py", line 51, in <module>
lr.fit(tr_x,tr_y)
File "F:\Python_Project\machine_learning_project_01\lib\site-packages\sklearn\linear_model\base.py", line 458, in fit
y_numeric=True, multi_output=True)
File "F:\Python_Project\machine_learning_project_01\lib\site-packages\sklearn\utils\validation.py", line 756, in check_X_y
estimator=estimator)
File "F:\Python_Project\machine_learning_project_01\lib\site-packages\sklearn\utils\validation.py", line 552, in check_array
"if it contains a single sample.".format(array))
ValueError: Expected 2D array, got 1D array instead:
array=[ 9.1802 5.8707 7.4239 13.176 7.0708 5.6397 18.959 5.0269 8.5186
21.279 5.7737 11.708 8.3829 6.3654 6.4296 6.8825 6.3534 7.4764
5.5204 8.8254 5.5277 7.9334 22.203 5.3077 5.734 8.0959 5.5649
7.6031 14.164 9.2482 5.7077 9.3102 5.0365 5.8918 9.7687 5.3794
6.5479 6.1891 5.2524 7.5402 8.2934 13.394 10.136 20.27 7.6366
7.2259 10.274 12.828 12.836 5.8014 5.4069 8.2951 9.4536 8.4084
7.3345 5.6063 5.4901 6.5159 5.7107 5.3054 5.4994 7.2182 11.7
7.0931].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.

from sklearn.linear_model import LinearRegression
lr = LinearRegression()
tr_x = np.array(tr_x).reshape(1,-1)
te_x = np.array(te_x).reshape(1,-1)
tr_y = np.array(tr_y).reshape(1,-1)
te_y = np.array(te_y).reshape(1,-1)
print(tr_x.shape,tr_y.shape)
lr.fit(tr_x,tr_y)