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Support pinned memory in the DataLoader #265

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Merged
colesbury merged 1 commit into from
Nov 29, 2016
Merged

Support pinned memory in the DataLoader #265

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17 changes: 16 additions & 1 deletion test/test_dataloader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -92,6 +92,12 @@ def test_sequential(self):
def test_sequential_batch(self):
self._test_sequential(DataLoader(self.dataset, batch_size=2))

def test_sequential_pin_memory(self):
loader = DataLoader(self.dataset, batch_size=2, pin_memory=True)
for input, target in loader:
self.assertTrue(input.is_pinned())
self.assertTrue(target.is_pinned())

def test_shuffle(self):
self._test_shuffle(DataLoader(self.dataset, shuffle=True))

Expand All @@ -110,6 +116,12 @@ def test_shuffle_workers(self):
def test_shuffle_batch_workers(self):
self._test_shuffle(DataLoader(self.dataset, batch_size=2, shuffle=True, num_workers=4))

def test_shuffle_pin_memory(self):
loader = DataLoader(self.dataset, batch_size=2, shuffle=True, num_workers=4, pin_memory=True)
for input, target in loader:
self.assertTrue(input.is_pinned())
self.assertTrue(target.is_pinned())

def test_error(self):
self._test_error(DataLoader(ErrorDataset(100), batch_size=2, shuffle=True))

Expand All @@ -118,8 +130,9 @@ def test_error_workers(self):

def test_partial_workers(self):
"check that workers exit even if the iterator is not exhausted"
loader = iter(DataLoader(self.dataset, batch_size=2, num_workers=4))
loader = iter(DataLoader(self.dataset, batch_size=2, num_workers=4, pin_memory=True))
workers = loader.workers
pin_thread = loader.pin_thread
for i, sample in enumerate(loader):
if i == 3:
break
Expand All @@ -128,6 +141,8 @@ def test_partial_workers(self):
w.join(1.0) # timeout of one second
self.assertFalse(w.is_alive(), 'subprocess not terminated')
self.assertEqual(w.exitcode, 0)
pin_thread.join(1.0)
self.assertFalse(pin_thread.is_alive())


if __name__ == '__main__':
Expand Down
50 changes: 48 additions & 2 deletions torch/utils/data/dataloader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,11 @@
import collections
import sys
import traceback
import threading
if sys.version_info[0] == 2:
import Queue as queue
else:
import queue


class ExceptionWrapper(object):
Expand All @@ -19,6 +24,7 @@ def _worker_loop(dataset, index_queue, data_queue, collate_fn):
while True:
r = index_queue.get()
if r is None:
data_queue.put(None)
break
idx, batch_indices = r
try:
Expand All @@ -29,6 +35,23 @@ def _worker_loop(dataset, index_queue, data_queue, collate_fn):
data_queue.put((idx, samples))


def _pin_memory_loop(in_queue, out_queue):
while True:
r = in_queue.get()
if r is None:
break
if isinstance(r[1], ExceptionWrapper):
out_queue.put(r)
continue
idx, batch = r
try:
batch = pin_memory_batch(batch)
except Exception:
out_queue.put((idx, ExceptionWrapper(sys.exc_info())))
else:
out_queue.put((idx, batch))


def default_collate(batch):
"Puts each data field into a tensor with outer dimension batch size"
if torch.is_tensor(batch[0]):
Expand All @@ -49,6 +72,15 @@ def default_collate(batch):
.format(type(batch[0]))))


def pin_memory_batch(batch):
if torch.is_tensor(batch):
return batch.pin_memory()
elif isinstance(batch, collections.Iterable):
return [pin_memory_batch(sample) for sample in batch]
else:
return batch


class DataLoaderIter(object):
"Iterates once over the DataLoader's dataset, as specified by the sampler"

Expand All @@ -58,6 +90,7 @@ def __init__(self, loader):
self.collate_fn = loader.collate_fn
self.sampler = loader.sampler
self.num_workers = loader.num_workers
self.pin_memory = loader.pin_memory

self.samples_remaining = len(self.sampler)
self.sample_iter = iter(self.sampler)
Expand All @@ -81,6 +114,15 @@ def __init__(self, loader):
w.daemon = True # ensure that the worker exits on process exit
w.start()

if self.pin_memory:
in_data = self.data_queue
self.data_queue = queue.Queue()
self.pin_thread = threading.Thread(
target=_pin_memory_loop,
args=(in_data, self.data_queue))
self.pin_thread.daemon = True
self.pin_thread.start()

# prime the prefetch loop
for _ in range(2 * self.num_workers):
self._put_indices()
Expand All @@ -94,7 +136,10 @@ def __next__(self):
if self.samples_remaining == 0:
raise StopIteration
indices = self._next_indices()
return self.collate_fn([self.dataset[i] for i in indices])
batch = self.collate_fn([self.dataset[i] for i in indices])
if self.pin_memory:
batch = pin_memory_batch(batch)
return batch

# check if the next sample has already been generated
if self.rcvd_idx in self.reorder_dict:
Expand Down Expand Up @@ -166,11 +211,12 @@ class DataLoader(object):
"""

def __init__(self, dataset, batch_size=1, shuffle=False, sampler=None,
num_workers=0, collate_fn=default_collate):
num_workers=0, collate_fn=default_collate, pin_memory=False):
self.dataset = dataset
self.batch_size = batch_size
self.num_workers = num_workers
self.collate_fn = collate_fn
self.pin_memory = pin_memory

if sampler is not None:
self.sampler = sampler
Expand Down