小编seb*_*-sz的帖子

我想从预训练的 Keras 模型中删除前N层。例如， an EfficientNetB0，其前3层仅负责预处理：

import tensorflow as tf

efinet = tf.keras.applications.EfficientNetB0(weights=None, include_top=True)

print(efinet.layers[:3])
# [<tensorflow.python.keras.engine.input_layer.InputLayer at 0x7fa9a870e4d0>,
# <tensorflow.python.keras.layers.preprocessing.image_preprocessing.Rescaling at 0x7fa9a61343d0>,
# <tensorflow.python.keras.layers.preprocessing.normalization.Normalization at 0x7fa9a60d21d0>]

正如M.Innat提到的，第一层是Input Layer，应该保留或重新附加。我想删除这些层，但是像这样的简单方法会引发错误：

import tensorflow as tf

efinet = tf.keras.applications.EfficientNetB0(weights=None, include_top=True)

print(efinet.layers[:3])
# [<tensorflow.python.keras.engine.input_layer.InputLayer at 0x7fa9a870e4d0>,
# <tensorflow.python.keras.layers.preprocessing.image_preprocessing.Rescaling at 0x7fa9a61343d0>,
# <tensorflow.python.keras.layers.preprocessing.normalization.Normalization at 0x7fa9a60d21d0>]

这将导致：

ValueError: Graph disconnected: cannot obtain value for tensor KerasTensor(...)

推荐的方法是什么？