Problem in the generator named 'data_generator' and the corresponding generators in 'data_loader.py' file

[ShubhayuDas]

I got an error at the very last section of the w_net_walk_through.ipynb file :

  2 depthmaps = []
  3 for i in tqdm(range(1)):

----> 4 dat = data_generator.next()
5
6 disparity_map_left, disparity_map_right = disp_maps_forward.predict(dat[0][0:10])

AttributeError: 'generator' object has no attribute 'next'

After going through https://stackoverflow.com/questions/1073396/is-generator-next-visible-in-python-3-0 , I found that on python 3 you need to use data_generator.next() or next(data_generator).

Note: I had to change this in the walk_through.ipynb file and the data_loader.py file as well

But even after this I get a Type Error:

TypeError: 'float' object cannot be interpreted as an integer

Here is the output:

TypeError Traceback (most recent call last)
in ()
2 depthmaps = []
3 for i in tqdm(range(1)):
----> 4 dat = data_generator.next()
5
6 disparity_map_left, disparity_map_right = disp_maps_forward.predict(dat[0][0:10])

~/PycharmProjects/tensorplay/venv/w-net-master/data_loader.py in train_generator_func()
50 def train_generator_func():
51 while True:
---> 52 X = train_generator1.next(self)
53 Y1 = train_generator2.next(self)
54 yield X, [Y1, np.zeros(shape=(Y1.shape[0], img_rows - 4, img_cols - 4)),

~/PycharmProjects/tensorplay/venv/lib/python3.6/site-packages/keras_preprocessing/image.py in next(self)
1817 # The transformation of images is not under thread lock
1818 # so it can be done in parallel
-> 1819 return self._get_batches_of_transformed_samples(index_array)

~/PycharmProjects/tensorplay/venv/lib/python3.6/site-packages/keras_preprocessing/image.py in _get_batches_of_transformed_samples(self, index_array)
1763 batch_x = np.zeros(
1764 (len(index_array),) + self.image_shape,
-> 1765 dtype=backend.floatx())
1766 # build batch of image data
1767 for i, j in enumerate(index_array):

TypeError: 'float' object cannot be interpreted as an integer

I am unable to fix this. Please help..

[tv12345]

Managed to solve it by downgrading numpy to 1.11.0.