I'm not sure if this is the correct forum thread but since the first week deals with the setup I figured I'd ask my question here (feel free to move it if there is a more appropriate thread).
So I just started with the MOOC and not being in the US I didn't want to go with an Amazon account (the exchange rate makes it quite expensive) so I figured I could do the first testing on my local machine and only when I get to the point where I want to run through the whole data set, I'd create an Amazon account and spin up the server.
However I'm having issues just running through the sample data-set. I created a sample of 100 cats and 100 dogs as suggested in the video. I started out with a batch size of 64 and went down to 32. 16 and finally 8. Here is my code:
# Grab the images in batches for the training and validaton process.
training_batches = vgg.get_batches(path + 'train', batch_size = batch_size)
validation_batches = vgg.get_batches(path + 'valid', batch_size = batch_size * 2)
vgg.fit(training_batches, validation_batches, nb_epoch=1)
I'm expecting to see the "Done!" message printed out, but the script never seems to reach this point. I just get the following and then nothing:
Found 160 images belonging to 2 classes.
Found 40 images belonging to 2 classes.
I do get the following warning when I run the code, so I'm suspecting a setup fault on my part:
Anaconda2\lib\site-packages\keras\layers\core.py:622: UserWarning: `output_shape` argument not specified for layer lambda_6 and cannot be automatically inferred with the Theano backend. Defaulting to output shape `(None, 3, 224, 224)` (same as input shape). If the expected output shape is different, specify it via the `output_shape` argument.
Unfortunately googling the warning did not help me much.
I did change Keras to use Theano, but other than that I'm using default configurations on everything. Here is what my keras.json file looks like:
I don't think the issue is my hardware since my GPU is fairly new; I had to replace it last year and went with a Nvidia 1060.
Any idea what I might be missing?