Open wiwatarm opened 6 years ago
@wiwatarm thanks for this issue. is inception_trained.h5
trained using MXNet backend?
Also the version of keras and mxnet you are using would be helpful.
use pip list | grep mxnet
in command line or import keras
and keras.__version__
@wiwatarm thanks for this issue. is
inception_trained.h5
trained using MXNet backend?Also the version of keras and mxnet you are using would be helpful. use
pip list | grep mxnet
in command line orimport keras
andkeras.__version__
thanks for the answer my keras version is '2.2.2', and no, the model has been trained by keras-tensorflow backend.
@wiwatarm unfortunately, mxnet backend does not support load weights trained using other backends yet. You need to pre-train using mxnet backend and load it for fine-tuning
@roywei Thank you for your answer. It makes sense. That said, is there a chance that this functionality is supported? For example, even the relatively innocuous:
>>> from keras.applications.inception_v3 import InceptionV3
# Using MXNet backend
>>> InceptionV3_base_model = InceptionV3(weights="imagenet", include_top=False)
kills the code, so we canot use standard pre-trained keras models directly.
(keras-mxnet==2.2.4.2
)
Hi! I'm using Keras-Mxnet backend (Keras version 2.1.6). When I started Keras, I used this command
KERAS_BACKEND=mxnet python
to start python. here is my following code. Usually, it worked just fine with Keras-tensorflow backend, but I have no idea where it has started to fail.I tried to fix it by infer to models.Layers.input = (256,256,3), but did not work.