我正在尝试使用自定义回调在训练期间访问模型中间层的预测。以下实际代码的精简版本演示了该问题。
import tensorflow as tf
import numpy as np
class Model(tf.keras.Model):
def __init__(self, input_shape=None, name="cus_model", **kwargs):
super(Model, self).__init__(name=name, **kwargs)
def build(self, input_shape):
self.dense1 = tf.keras.layers.Dense(input_shape=input_shape, units=32)
def call(self, input_tensor):
return self.dense1(input_tensor)
class CustomCallback(tf.keras.callbacks.Callback):
def on_epoch_end(self, epoch, logs=None):
get_output = tf.keras.backend.function(
inputs = self.model.layers[0].input,
outputs = self.model.layers[0].output
)
print("Layer output: ",get_output.outputs)
X = np.ones((8,16))
y = np.sum(X, axis=1)
model = Model()
model.compile(optimizer='adam',loss='mean_squared_error', metrics='accuracy')
model.fit(X,y, epochs=8, callbacks=[CustomCallback()])
回调是按照此 answer 中的建议编写的。得到以下错误:<ipython-input-3-635fd53dbffc> in on_epoch_end(self, epoch, logs)
12 def on_epoch_end(self, epoch, logs=None):
13 get_output = tf.keras.backend.function(
---> 14 inputs = self.model.layers[0].input,
15 outputs = self.model.layers[0].output
16 )
.
.
AttributeError: Layer dense is not connected, no input to return.
这是什么原因造成的?如何解决?
最佳答案
由于相同的错误,我也无法获得 self.layers[0].input
,但也许您可以像这样直接调用 Model
中定义的函数:
class Model(tf.keras.Model):
def __init__(self, input_shape=None, name="cus_model", **kwargs):
super(Model, self).__init__(name=name, **kwargs)
if not input_shape:
input_shape = (10,)
self.dense1 = tf.keras.layers.Dense(input_shape=input_shape, units=32)
self.dev_dataset = np.ones((8,16))
def call(self, input_tensor):
return self.dense1(input_tensor)
class CustomCallback(tf.keras.callbacks.Callback):
def on_epoch_end(self, epoch, logs=None):
self.model.call(self.model.dev_dataset)
X = np.ones((8,16))
y = np.sum(X, axis=1)
model = Model()
model.compile(optimizer='adam',loss='mean_squared_error', metrics='accuracy')
model.fit(X,y, epochs=1, callbacks=[CustomCallback()])
关于python - 尝试使用 tensorflow 自定义回调进行中间层预测时出现 "Layer is not connected, no input to return"错误,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/62654908/