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Tag: tensorflow

AttributeError: module ‘keras.preprocessing.image’ has no attribute ‘img_to_array’

I have added following libraries and half part of the code is executing. In second half I get this error. Libraries added: Error: AttributeError: module ‘keras.preprocessing.image’ has no attribute ‘img_to_array’ I was following this code and changes the libraries too still can’t resolve the issue. Answer It has now moved to tf.keras.utils.img_to_array. See the docs

Save keras preprocessing layer

I have a model where I’m doing different preprocessing, outside the model itself. One part of the preprocessing is using a category encoder based on keras with: I apply this than with to my pandas dataframe. Now I want to store my model and in order to store the model I also have to store the 2 preprocessing layers cat_index

Is passing activity_regularizer as argument to Conv2D() the same as passing it seperately right after Conv2D()? (Tensorflow)

I was wondering whether creating the model by passing activity_regularizer=’l1_l2′ as an argument to Conv2D() will mathematically make a difference to creating the model by adding model.add(ActivityRegularization(l1=…, l2=…)) seperately? For me, it is hard to tell, as training always involves some randomness. But the results seem similar. One additional question I have is: I accidentally passed the activity_regularizer=’l1_l2′ argument to

Obtaining the parameters of layers after concatenation in Keras

I’m trying to get the output and input parameters after concatenation in keras, more specifically in “concat_” and “hidden 6” layers. Is there way to obtain the parameters by layer name? Also, is there any way to run the model (after training) until the concatenation point? Answer You could give each layer that you want to later retrieve, a specific