def test_shuffle(self):
"""Simple test to ensure that dataloader is initialized with correct
data sampler
"""
dts = ['train', 'valid', 'test']
exts = ['', ':stream', ':ordered', ':stream:ordered']
shuffle_opts = [False, True]
task = 'babi:task1k:1'
for dt in dts:
for ext in exts:
datatype = dt + ext
for shuffle in shuffle_opts:
opt_defaults = {
'pytorch_teacher_task': task,
'datatype': datatype,
'shuffle': shuffle
}
with testing_utils.capture_output() as _:
parser = display_setup_args()
parser.set_defaults(**opt_defaults)
opt = parser.parse_args()
teacher = create_task_agent_from_taskname(opt)[0]
if ('ordered' in datatype or
('stream' in datatype and not opt.get('shuffle'))
or 'train' not in datatype):
self.assertIsInstance(
teacher.pytorch_dataloader.sampler, Sequential,
'PytorchDataTeacher failed with args: {}'.
format(opt))
else:
self.assertIsInstance(
teacher.pytorch_dataloader.sampler,
RandomSampler,
'PytorchDataTeacher failed with args: {}'.
format(opt))
def test_pytd_teacher(self):
"""
Test that the pytorch teacher works with given Pytorch Datasets
as well
I'll be using the Flickr30k dataset to ensure that the observations
are the same.
"""
defaults = parser_defaults.copy()
defaults['datatype'] = 'train:stream'
defaults['image_mode'] = 'ascii'
f = io.StringIO()
with redirect_stdout(f):
# Get processed act from agent
parser = display_setup_args()
defaults['pytorch_teacher_dataset'] = 'flickr30k'
del defaults['pytorch_teacher_task']
parser.set_defaults(**defaults)
opt = parser.parse_args()
teacher = create_task_agent_from_taskname(opt)[0]
pytorch_teacher_act = teacher.act()
parser = display_setup_args()
defaults['task'] = 'flickr30k'
del defaults['pytorch_teacher_dataset']
parser.set_defaults(**defaults)
opt = parser.parse_args()
teacher = create_task_agent_from_taskname(opt)[0]
regular_teacher_act = teacher.act()
keys = set(pytorch_teacher_act.keys()).intersection(
set(regular_teacher_act.keys()))
self.assertTrue(len(keys) != 0)
for key in keys:
self.assertTrue(
pytorch_teacher_act[key] == regular_teacher_act[key],
'PytorchDataTeacher does not have the same value '
'as regular teacher for act key: {}'.format(key))
print('\n------Passed `test_pytd_teacher`------\n')
def run_display_test(defaults, ep_and_ex_counts):
with testing_utils.capture_output() as f:
parser = display_setup_args()
parser.set_defaults(**defaults)
opt = parser.parse_args()
display_data(opt)
str_output = f.getvalue()
self.assertTrue(
'[ loaded {} episodes with a total of {} examples ]'.format(
ep_and_ex_counts[0], ep_and_ex_counts[1]) in str_output,
'PytorchDataTeacher multitasking failed with '
'following args: {}'.format(opt))
def test_pytd_teacher(self):
"""
Test that the pytorch teacher works with given Pytorch Datasets
as well
"""
defaults = integration_test_parser_defaults.copy()
defaults['datatype'] = 'train:stream'
defaults['image_mode'] = 'ascii'
with testing_utils.capture_output():
# Get processed act from agent
parser = display_setup_args()
defaults['pytorch_teacher_dataset'] = 'integration_tests'
del defaults['pytorch_teacher_task']
parser.set_defaults(**defaults)
opt = parser.parse_args()
teacher = create_task_agent_from_taskname(opt)[0]
pytorch_teacher_act = teacher.act()
parser = display_setup_args()
defaults['task'] = 'integration_tests'
del defaults['pytorch_teacher_dataset']
parser.set_defaults(**defaults)
opt = parser.parse_args()
teacher = create_task_agent_from_taskname(opt)[0]
regular_teacher_act = teacher.act()
keys = set(pytorch_teacher_act.keys()).intersection(
set(regular_teacher_act.keys()))
self.assertTrue(len(keys) != 0)
for key in keys:
self.assertTrue(
pytorch_teacher_act[key] == regular_teacher_act[key],
'PytorchDataTeacher does not have the same value '
'as regular teacher for act key: {}. '
'Values: {}; {}'.format(key, pytorch_teacher_act[key],
regular_teacher_act[key]),
)
def test_shuffle(self):
"""Simple test to ensure that dataloader is initialized with correct
data sampler
"""
dts = ['train', 'valid', 'test']
exts = ['', ':stream', ':ordered', ':stream:ordered']
shuffle_opts = [False, True]
task = 'babi:task1k:1'
for dt in dts:
for ext in exts:
datatype = dt + ext
for shuffle in shuffle_opts:
opt_defaults = {
'pytorch_teacher_task': task,
'datatype': datatype,
'shuffle': shuffle
}
print('Testing test_shuffle with args {}'.format(
opt_defaults))
f = io.StringIO()
with redirect_stdout(f):
parser = display_setup_args()
parser.set_defaults(**opt_defaults)
opt = parser.parse_args()
teacher = create_task_agent_from_taskname(opt)[0]
if ('ordered' in datatype or
('stream' in datatype and not opt.get('shuffle'))
or 'train' not in datatype):
self.assertTrue(
type(teacher.pytorch_dataloader.sampler) is
Sequential,
'PytorchDataTeacher failed with args: {}'.format(
opt))
else:
self.assertTrue(
type(teacher.pytorch_dataloader.sampler) is
RandomSampler,
'PytorchDataTeacher failed with args: {}'.format(
opt))
print('\n------Passed `test_shuffle`------\n')
