class HMDBMixValidIterator:
stochastic = False
def __init__(self, dataset=None, batch_size=None, num_batches=None,
data_specs=False, return_tuple=False, rng=None):
self._hmdb_iterator = HMDBIterator(dataset._hmdb, batch_size,
num_batches,
data_specs, return_tuple,
rng)
self._dvd_iterator = AtousaDatasetIterator(dataset._dvd, batch_size,
num_batches,
data_specs, return_tuple,
rng)
self.num_examples = self._hmdb_iterator.num_examples + self._dvd_iterator.num_examples
self.cur = 0
self.batch_size = batch_size
self.dataset = dataset
self.hmdb_stop = False
self.dvd_stop = False
def __iter__(self):
return self
def next(self):
print(self.hmdb_stop, self.cur, self.num_examples)
if not self.hmdb_stop and self.cur % 2 == 0:
print "herehmdb"
try:
x,y = self._hmdb_iterator.next()
except:
self.hmdb_stop = True
if self.dvd_stop:
raise StopIteration()
else:
return self.next()
else:
try:
print "heredvd"
x, y_tmp = self._dvd_iterator.next()
except:
self.dvd_stop = True
if self.hmdb_stop:
raise StopIteration()
else:
return self.next()
### Adapt labels
y = np.zeros((self.batch_size, 51)).astype(config.floatX)
for i in xrange(0, self.batch_size):
for j in xrange(0, len(self.dataset.label_transfer)):
y[i, self.dataset.label_transfer[j, 1]] = y_tmp[i, self.dataset.label_transfer[j, 0]]
self.cur = self.cur + 1
return x, y
def __init__(self,
dataset=None,
batch_size=None,
num_batches=None,
data_specs=False,
return_tuple=False,
rng=None):
self._hmdb_iterator = HMDBIterator(dataset._hmdb, batch_size,
num_batches, data_specs,
return_tuple, rng)
self._dvd_iterator = AtousaDatasetIterator(dataset._dvd, batch_size,
num_batches, data_specs,
return_tuple, rng)
self.num_examples = self._hmdb_iterator.num_examples + self._dvd_iterator.num_examples
self.cur = 0
self.batch_size = batch_size
self.dataset = dataset
self.hmdb_stop = False
self.dvd_stop = False
def __init__(self, dataset=None, batch_size=None, num_batches=None,
data_specs=False, return_tuple=False, rng=None):
self._hmdb_iterator = HMDBIterator(dataset._hmdb, batch_size,
num_batches,
data_specs, return_tuple,
rng)
self._dvd_iterator = AtousaDatasetIterator(dataset._dvd, batch_size,
num_batches,
data_specs, return_tuple,
rng)
self.num_examples = self._hmdb_iterator.num_examples + self._dvd_iterator.num_examples
self.cur = 0
self.batch_size = batch_size
self.dataset = dataset
self.hmdb_stop = False
self.dvd_stop = False
class HMDBMixValidIterator:
stochastic = False
def __init__(self,
dataset=None,
batch_size=None,
num_batches=None,
data_specs=False,
return_tuple=False,
rng=None):
self._hmdb_iterator = HMDBIterator(dataset._hmdb, batch_size,
num_batches, data_specs,
return_tuple, rng)
self._dvd_iterator = AtousaDatasetIterator(dataset._dvd, batch_size,
num_batches, data_specs,
return_tuple, rng)
self.num_examples = self._hmdb_iterator.num_examples + self._dvd_iterator.num_examples
self.cur = 0
self.batch_size = batch_size
self.dataset = dataset
self.hmdb_stop = False
self.dvd_stop = False
def __iter__(self):
return self
def next(self):
print(self.hmdb_stop, self.cur, self.num_examples)
if not self.hmdb_stop and self.cur % 2 == 0:
print "herehmdb"
try:
x, y = self._hmdb_iterator.next()
except:
self.hmdb_stop = True
if self.dvd_stop:
raise StopIteration()
else:
return self.next()
else:
try:
print "heredvd"
x, y_tmp = self._dvd_iterator.next()
except:
self.dvd_stop = True
if self.hmdb_stop:
raise StopIteration()
else:
return self.next()
### Adapt labels
y = np.zeros((self.batch_size, 51)).astype(config.floatX)
for i in xrange(0, self.batch_size):
for j in xrange(0, len(self.dataset.label_transfer)):
y[i, self.dataset.label_transfer[j, 1]] = y_tmp[
i, self.dataset.label_transfer[j, 0]]
self.cur = self.cur + 1
return x, y
