So I think tensorflow.keras and the independant keras packages are in conflict and I can't load my model, which I have made with transfer learning. Import in the CNN ipynb:
!pip install tensorflow-gpu==2.0.0b1
import tensorflow as tf
from tensorflow import keras
print(tf.__version__)
Loading this pretrained model
base_model = keras.applications.xception.Xception(weights="imagenet",
include_top=False)
avg = keras.layers.GlobalAveragePooling2D()(base_model.output)
output = keras.layers.Dense(n_classes, activation="softmax")(avg)
model = keras.models.Model(inputs=base_model.input, outputs=output)
Saving with:
model.save('Leavesnet Model 2.h5')
Then in the new ipynb for the already trained model (the imports are the same as in the CNN ipynb:
from keras.models import load_model
model =load_model('Leavesnet Model.h5')
I get the error:
AttributeError Traceback (most recent call last)
<ipython-input-4-77ca5a1f5f24> in <module>()
2 from keras.models import load_model
3
----> 4 model =load_model('Leavesnet Model.h5')
13 frames
/usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py in placeholder(shape, ndim, dtype, sparse, name)
539 x = tf.sparse_placeholder(dtype, shape=shape, name=name)
540 else:
--> 541 x = tf.placeholder(dtype, shape=shape, name=name)
542 x._keras_shape = shape
543 x._uses_learning_phase = False
AttributeError: module 'tensorflow' has no attribute 'placeholder'
I think there might be a conflict between tf.keras and the independant keras, can someone help me out?
Yes, there is a conflict between tf.keras and keras packages, you trained the model using tf.keras but then you are loading it with the keras package. That is not supported, you should use only one version of this package.
The specific problem is that you are using TensorFlow 2.0, but the standalone keras package does not support TensorFlow 2.0 yet.