The Added Layer Must Be An Instance Of Class Layer. Found:
Solution 1:
This won't work because a tensorflow.keras layer is getting added to a keras Model.
vgg_model = tensorflow.keras.applications.vgg16.VGG16()
model = keras.Sequential()
model.add(vgg_model.layers[0])
Instantiate tensorflow.keras.Sequential(). This will work.
model = tensorflow.keras.Sequential()
model.add(vgg_model.layers[0])
Solution 2:
Adding to @Manoj Mohan's answer, you can add an input_layer
to your model
using input_layer
from Keras
layers
as below:
import keras
from keras.modelsimportSequentialfrom keras.layersimportInputLayer
model = Sequential()
model.add(InputLayer(input_shape=shape, name=name))
....
if you are using the TensorFlow
builtin Keras
then import is different other things are still the same
import tensorflow as tf
import tensorflow.kerasas keras
from tensorflow.keras.modelsimportSequentialfrom tensorflow.keras.layersimportInputLayer
model = Sequential()
model.add(InputLayer(input_shape=shape, name=name))
....
Coming to the main part, if you want to import layers to your sequential model, you can use the following syntax.
import keras
from keras.models import Sequential, load_model
from keras import optimizers
from keras.applications.vgg16 import VGG16
from keras.applications.vgg19 import VGG19
# For VGG16 loading to sequential model
model = Sequential(VGG16().layers)
# For VGG19 loading to sequential model
model = Sequential(VGG19().layers)
Solution 3:
You do not need to create an InputLayer, you simply must import the BatchNormalization layer in the same manner as your Conv2D/other layers, e.g:
from tensorflow.keras.layersimportConv2D, Flatten, MaxPooling2D, Dropout, BatchNormalization
Instead of importing it as an independent Keras layer, i.e:
from tensorflow.keras.layersimportConv2D, Flatten, MaxPooling2D, Dropoutfrom keras.layersimportBatchNormalization
Solution 4:
The above code snippet works for TensorFlow
version 2.x
. You can run the above snippet by upgrading your TensorFlow using the following command:
pip install --upgrade tensorflow
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