import tensorflow as tf
import numpy as np
随机删除神经元,防止过度拟合
tf.random.set_seed(0)
layer = tf.keras.layers.Dropout(
.2, # 0~1之间的小数。要丢弃的输入数据的比例。
input_shape=(2, ))
print(layer)
<tensorflow.python.keras.layers.core.Dropout object at 0x0000021CF0A03820>
inputs = np.arange(10).reshape(5, 2).astype(np.float32)
print(inputs)
[[0. 1.] [2. 3.] [4. 5.] [6. 7.] [8. 9.]]
outputs = layer(inputs, training=True)
print(outputs)
tf.Tensor( [[ 0. 1.25] [ 2.5 3.75] [ 5. 6.25] [ 7.5 8.75] [10. 0. ]], shape=(5, 2), dtype=float32)