Hello,

I’m trying to concatenate 2 numpy arrays of features predicted by the convolution layers in a vgg16 model.

Basically i have used the bottom layers of a vgg16 model to predict the features for my full dataset and now I want to load the parts of dataset dynamically based on some settings from a dict, to train some models with it.

So, I have 2 array of shape:

`(724, 512, 6, 8) and (3376, 512, 6, 8)`

Basically the first one contains features predicted from 724 image files (each prediction has shape (512, 6, 8)).

I want to concatenate these 2 arrays into one of shape (4100, 512, 6, 8)

I have tried using:

np.array([np.concatenate(arr, axis=0) for arr in false_train_list])

where false_train_list is the list containing the 2 arrays with the above shapes.

Also tried with np.stack, tf.stack, etc…

All of these result in an array with shape (2,)

Can someone explain why ? I haven’t found any good resources to understand how exactly np.concatenate() works…

Thank you!