tensorflow - Yield ValueError: Too many vaues to unpack (expected 2) in python

Question

I have an issue trying to implement the regression solution proposed in this thread.

Using Keras ImageDataGenerator in a regression model

Another stack question had a similar issue: Tensorflow ValueError: Too many vaues to unpack (expected 2) but I couldnt find a solution that would work in my case. I went through this explanation for yield without any result. What is odd to me is that the first two loops complete but it crashes on the third when the outputs are identical.

For the directory, the folders are labeled 0, 1, and 2 corresponding to the 0.1, 0.3, and 0.5, respectively in the list_of_values.

import numpy as np
from keras.preprocessing.image import ImageDataGenerator      
train_datagen = ImageDataGenerator(
            rescale=1./255,
            height_shift_range=0.15,
            shear_range=0.2)
def regression_flow_from_directory(flow_from_directory_gen, list_of_values):
    for x, y in flow_from_directory_gen:
        print (list_of_values[y], list_of_values,y)
        yield (x, list_of_values[y])
batch_size=3
list_of_values=[0.1,0.3,0.5]
(x_train,y_train) = regression_flow_from_directory(train_datagen.flow_from_directory(
                'figs/train',  # this is the target directory
                batch_size=batch_size,
                class_mode='sparse'),
                np.asarray(list_of_values)) 

output

Found 9 images belonging to 3 classes.
[ 0.5  0.3  0.1] [ 0.1  0.3  0.5] [2 1 0]
[ 0.3  0.1  0.3] [ 0.1  0.3  0.5] [1 0 1]
[ 0.5  0.5  0.1] [ 0.1  0.3  0.5] [2 2 0]
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-179-3cf97453bd05> in <module>()
      5         batch_size=batch_size,
      6         class_mode='sparse'),
----> 7         np.asarray(list_of_values))  

ValueError: too many values to unpack (expected 2)

EDIT: the Error was in returning the function regression_flow_from_directory to two variables (x_train, y_train). Returning only to x_train passes the generator correctly.

x_train = regression_flow_from_directory(train_datagen.flow_from_directory(
        'figs/train',  # this is the target directory
        batch_size=batch_size,
        class_mode='sparse'),
        np.asarray(list_of_values)) 

Answer 1

The error has nothing to do with np.asarray. The function regression_flow_from_directory contains a yield statement. Therefore when you call it you get, not a tuple of yielded values, but a generator object. That's just one object, which you are trying to unpack into a two-element tuple. That's the reason for the error message.