interpolation='nearest',
aspect='auto')
# Plot!
plt.show()
exit()
if __name__ == '__main__':
""" Tests CNN_LSTM on SortOfCLEVR"""
# "Loaded parameters".
from miprometheus.utils.param_interface import ParamInterface
from miprometheus.utils.app_state import AppState
app_state = AppState()
app_state.visualize = True
from miprometheus.problems.image_text_to_class.sort_of_clevr import SortOfCLEVR
problem_params = ParamInterface()
problem_params.add_config_params({
'data_folder': '~/data/sort-of-clevr/',
'split': 'train',
'regenerate': False,
'dataset_size': 10000,
'img_size': 128
})
# create problem
sortofclevr = SortOfCLEVR(problem_params)
batch_size = 64
print(type(image))
plt.imshow(image.permute(1, 2, 0),
interpolation='nearest', aspect='auto')
# Plot!
plt.show()
if __name__ == '__main__':
""" Tests MultiHopsStackedAttentionNetwork on ShapeColorQuery"""
# "Loaded parameters".
from miprometheus.utils.param_interface import ParamInterface
from miprometheus.utils.app_state import AppState
app_state = AppState()
app_state.visualize = False
from miprometheus.problems import ShapeColorQuery
problem_params = ParamInterface()
problem_params.add_config_params({'data_folder': '~/data/shape-color-query/',
'split': 'train',
'regenerate': False,
'dataset_size': 10000,
'img_size': 128})
# create problem
shapecolorquery = ShapeColorQuery(problem_params)
batch_size = 64
# wrap DataLoader on top of this Dataset subclass
from torch.utils.data import DataLoader
