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[英]TypeError: 'module' object is not callable Tensorboard in Keras
[英]TypeError: 'module' object is not callable. keras
系統信息
-Windows 10
-TensorFlow后端(是/否):是
-TensorFlow版本:1.14.0
-Keras版本:2.24
-Python版本:3.6
-CUDA / cuDNN版本:10
-GPU型號和內存:gtx 1050 ti
描述當前行為
我通過conda安裝了tensoflow和keras。 然后我嘗試運行此代碼:
import tensorflow as tf
import keras
import numpy as np
model = keras.Sequential([keras.layers(units=1, input_shape=[1])])
model.compile(optimizer="sgd", loss="mean_squared_error")
x = np.array([-1, 0, 1, 2, 3, 4])
y = np.array([-3, -1, 1, 3, 5, 7])
model.fit(x, y, epochs=500)
print(model.predict([10]))`
當我運行此代碼時,出現錯誤:
Using TensorFlow backend.
Traceback (most recent call last):
File "C:/Users/xxx/PycharmProjects/Workspace/tensorflow/hello_world_of_nn.py", line 5, in <module>
model = keras.Sequential([keras.layers(units=1, input_shape=[1])])
TypeError: 'module' object is not callable
當我嘗試這個:
python -c 'import keras as k; print(k.__version__)'
我得到錯誤:
C:\Users\xxx>python -c 'import keras as k; print(k.__version__)'
File "<string>", line 1
'import
^
SyntaxError: EOL while scanning string literal
這應該很好:
import tensorflow as tf
import keras
import numpy as np
model = keras.models.Sequential([keras.layers.Dense(units=1, input_shape=[1])])
model.compile(optimizer="sgd", loss="mean_squared_error")
x = np.array([-1, 0, 1, 2, 3, 4])
y = np.array([-3, -1, 1, 3, 5, 7])
model.fit(x, y, epochs=500)
print(model.predict([10]))
請注意keras.models.Sequential
和keras.layers.Dense
的用法。
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