zhreshold closed pull request #13550: Fixes infinite loop using imagedetiter
URL: https://github.com/apache/incubator-mxnet/pull/13550
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diff --git a/python/mxnet/image/detection.py b/python/mxnet/image/detection.py
index b27917c8623..d5b5ecab528 100644
--- a/python/mxnet/image/detection.py
+++ b/python/mxnet/image/detection.py
@@ -658,19 +658,26 @@ class ImageDetIter(ImageIter):
Data name for provided symbols.
label_name : str
Name for detection labels
+ last_batch_handle : str, optional
+ How to handle the last batch.
+ This parameter can be 'pad'(default), 'discard' or 'roll_over'.
+ If 'pad', the last batch will be padded with data starting from the
begining
+ If 'discard', the last batch will be discarded
+ If 'roll_over', the remaining elements will be rolled over to the next
iteration
kwargs : ...
More arguments for creating augmenter. See mx.image.CreateDetAugmenter.
"""
def __init__(self, batch_size, data_shape,
path_imgrec=None, path_imglist=None, path_root=None,
path_imgidx=None,
shuffle=False, part_index=0, num_parts=1, aug_list=None,
imglist=None,
- data_name='data', label_name='label', **kwargs):
+ data_name='data', label_name='label',
last_batch_handle='pad', **kwargs):
super(ImageDetIter, self).__init__(batch_size=batch_size,
data_shape=data_shape,
path_imgrec=path_imgrec,
path_imglist=path_imglist,
path_root=path_root,
path_imgidx=path_imgidx,
shuffle=shuffle,
part_index=part_index,
num_parts=num_parts, aug_list=[],
imglist=imglist,
- data_name=data_name,
label_name=label_name)
+ data_name=data_name,
label_name=label_name,
+ last_batch_handle=last_batch_handle)
if aug_list is None:
self.auglist = CreateDetAugmenter(data_shape, **kwargs)
@@ -751,14 +758,10 @@ def reshape(self, data_shape=None, label_shape=None):
self.provide_label = [(self.provide_label[0][0],
(self.batch_size,) + label_shape)]
self.label_shape = label_shape
- def next(self):
- """Override the function for returning next batch."""
+ def _batchify(self, batch_data, batch_label, start=0):
+ """Override the helper function for batchifying data"""
+ i = start
batch_size = self.batch_size
- c, h, w = self.data_shape
- batch_data = nd.zeros((batch_size, c, h, w))
- batch_label = nd.empty(self.provide_label[0][1])
- batch_label[:] = -1
- i = 0
try:
while i < batch_size:
label, s = self.next_sample()
@@ -783,7 +786,48 @@ def next(self):
if not i:
raise StopIteration
- return io.DataBatch([batch_data], [batch_label], batch_size - i)
+ return i
+
+ def next(self):
+ """Override the function for returning next batch."""
+ batch_size = self.batch_size
+ c, h, w = self.data_shape
+ # if last batch data is rolled over
+ if self._cache_data is not None:
+ # check both the data and label have values
+ assert self._cache_label is not None, "_cache_label didn't have
values"
+ assert self._cache_idx is not None, "_cache_idx didn't have values"
+ batch_data = self._cache_data
+ batch_label = self._cache_label
+ i = self._cache_idx
+ else:
+ batch_data = nd.zeros((batch_size, c, h, w))
+ batch_label = nd.empty(self.provide_label[0][1])
+ batch_label[:] = -1
+ i = self._batchify(batch_data, batch_label)
+ # calculate the padding
+ pad = batch_size - i
+ # handle padding for the last batch
+ if pad != 0:
+ if self.last_batch_handle == 'discard':
+ raise StopIteration
+ # if the option is 'roll_over', throw StopIteration and cache the
data
+ elif self.last_batch_handle == 'roll_over' and \
+ self._cache_data is None:
+ self._cache_data = batch_data
+ self._cache_label = batch_label
+ self._cache_idx = i
+ raise StopIteration
+ else:
+ _ = self._batchify(batch_data, batch_label, i)
+ if self.last_batch_handle == 'pad':
+ self._allow_read = False
+ else:
+ self._cache_data = None
+ self._cache_label = None
+ self._cache_idx = None
+
+ return io.DataBatch([batch_data], [batch_label], pad=pad)
def augmentation_transform(self, data, label): # pylint:
disable=arguments-differ
"""Override Transforms input data with specified augmentations."""
diff --git a/python/mxnet/image/image.py b/python/mxnet/image/image.py
index c9a457f5b7e..9c2a1cbfba2 100644
--- a/python/mxnet/image/image.py
+++ b/python/mxnet/image/image.py
@@ -1145,7 +1145,7 @@ def __init__(self, batch_size, data_shape, label_width=1,
self.shuffle = shuffle
if self.imgrec is None:
self.seq = imgkeys
- elif shuffle or num_parts > 1:
+ elif shuffle or num_parts > 1 or path_imgidx:
assert self.imgidx is not None
self.seq = self.imgidx
else:
@@ -1261,7 +1261,7 @@ def next(self):
i = self._cache_idx
# clear the cache data
else:
- batch_data = nd.empty((batch_size, c, h, w))
+ batch_data = nd.zeros((batch_size, c, h, w))
batch_label = nd.empty(self.provide_label[0][1])
i = self._batchify(batch_data, batch_label)
# calculate the padding
@@ -1285,6 +1285,7 @@ def next(self):
self._cache_data = None
self._cache_label = None
self._cache_idx = None
+
return io.DataBatch([batch_data], [batch_label], pad=pad)
def check_data_shape(self, data_shape):
diff --git a/tests/python/unittest/test_image.py
b/tests/python/unittest/test_image.py
index 4f66823cdbf..4063027cc1e 100644
--- a/tests/python/unittest/test_image.py
+++ b/tests/python/unittest/test_image.py
@@ -25,6 +25,7 @@
from nose.tools import raises
+
def _get_data(url, dirname):
import os, tarfile
download(url, dirname=dirname, overwrite=False)
@@ -50,6 +51,62 @@ def _generate_objects():
label = np.hstack((cid[:, np.newaxis], boxes)).ravel().tolist()
return [2, 5] + label
+def _test_imageiter_last_batch(imageiter_list, assert_data_shape):
+ test_iter = imageiter_list[0]
+ # test batch data shape
+ for _ in range(3):
+ for batch in test_iter:
+ assert batch.data[0].shape == assert_data_shape
+ test_iter.reset()
+ # test last batch handle(discard)
+ test_iter = imageiter_list[1]
+ i = 0
+ for batch in test_iter:
+ i += 1
+ assert i == 5
+ # test last_batch_handle(pad)
+ test_iter = imageiter_list[2]
+ i = 0
+ for batch in test_iter:
+ if i == 0:
+ first_three_data = batch.data[0][:2]
+ if i == 5:
+ last_three_data = batch.data[0][1:]
+ i += 1
+ assert i == 6
+ assert np.array_equal(first_three_data.asnumpy(),
last_three_data.asnumpy())
+ # test last_batch_handle(roll_over)
+ test_iter = imageiter_list[3]
+ i = 0
+ for batch in test_iter:
+ if i == 0:
+ first_image = batch.data[0][0]
+ i += 1
+ assert i == 5
+ test_iter.reset()
+ first_batch_roll_over = test_iter.next()
+ assert np.array_equal(
+ first_batch_roll_over.data[0][1].asnumpy(), first_image.asnumpy())
+ assert first_batch_roll_over.pad == 2
+ # test iteratopr work properly after calling reset several times when
last_batch_handle is roll_over
+ for _ in test_iter:
+ pass
+ test_iter.reset()
+ first_batch_roll_over_twice = test_iter.next()
+ assert np.array_equal(
+ first_batch_roll_over_twice.data[0][2].asnumpy(),
first_image.asnumpy())
+ assert first_batch_roll_over_twice.pad == 1
+ # we've called next once
+ i = 1
+ for _ in test_iter:
+ i += 1
+ # test the third epoch with size 6
+ assert i == 6
+ # test shuffle option for sanity test
+ test_iter = imageiter_list[4]
+ for _ in test_iter:
+ pass
+
class TestImage(unittest.TestCase):
IMAGES_URL = "http://data.mxnet.io/data/test_images.tar.gz";
@@ -151,86 +208,32 @@ def test_color_normalize(self):
assert_almost_equal(mx_result.asnumpy(), (src - mean) / std,
atol=1e-3)
def test_imageiter(self):
- def check_imageiter(dtype='float32'):
- im_list = [[np.random.randint(0, 5), x] for x in TestImage.IMAGES]
- fname = './data/test_imageiter.lst'
- file_list = ['\t'.join([str(k), str(np.random.randint(0, 5)), x])
- for k, x in enumerate(TestImage.IMAGES)]
- with open(fname, 'w') as f:
- for line in file_list:
- f.write(line + '\n')
-
- test_list = ['imglist', 'path_imglist']
+ im_list = [[np.random.randint(0, 5), x] for x in TestImage.IMAGES]
+ fname = './data/test_imageiter.lst'
+ file_list = ['\t'.join([str(k), str(np.random.randint(0, 5)), x])
+ for k, x in enumerate(TestImage.IMAGES)]
+ with open(fname, 'w') as f:
+ for line in file_list:
+ f.write(line + '\n')
+ test_list = ['imglist', 'path_imglist']
+ for dtype in ['int32', 'float32', 'int64', 'float64']:
for test in test_list:
imglist = im_list if test == 'imglist' else None
path_imglist = fname if test == 'path_imglist' else None
-
- test_iter = mx.image.ImageIter(2, (3, 224, 224),
label_width=1, imglist=imglist,
- path_imglist=path_imglist, path_root='', dtype=dtype)
- # test batch data shape
- for _ in range(3):
- for batch in test_iter:
- assert batch.data[0].shape == (2, 3, 224, 224)
- test_iter.reset()
- # test last batch handle(discard)
- test_iter = mx.image.ImageIter(3, (3, 224, 224),
label_width=1, imglist=imglist,
- path_imglist=path_imglist, path_root='', dtype=dtype,
last_batch_handle='discard')
- i = 0
- for batch in test_iter:
- i += 1
- assert i == 5
- # test last_batch_handle(pad)
- test_iter = mx.image.ImageIter(3, (3, 224, 224),
label_width=1, imglist=imglist,
- path_imglist=path_imglist, path_root='', dtype=dtype,
last_batch_handle='pad')
- i = 0
- for batch in test_iter:
- if i == 0:
- first_three_data = batch.data[0][:2]
- if i == 5:
- last_three_data = batch.data[0][1:]
- i += 1
- assert i == 6
- assert np.array_equal(first_three_data.asnumpy(),
last_three_data.asnumpy())
- # test last_batch_handle(roll_over)
- test_iter = mx.image.ImageIter(3, (3, 224, 224),
label_width=1, imglist=imglist,
- path_imglist=path_imglist, path_root='', dtype=dtype,
last_batch_handle='roll_over')
- i = 0
- for batch in test_iter:
- if i == 0:
- first_image = batch.data[0][0]
- i += 1
- assert i == 5
- test_iter.reset()
- first_batch_roll_over = test_iter.next()
- assert np.array_equal(
- first_batch_roll_over.data[0][1].asnumpy(),
first_image.asnumpy())
- assert first_batch_roll_over.pad == 2
- # test iteratopr work properly after calling reset several
times when last_batch_handle is roll_over
- for _ in test_iter:
- pass
- test_iter.reset()
- first_batch_roll_over_twice = test_iter.next()
- assert np.array_equal(
- first_batch_roll_over_twice.data[0][2].asnumpy(),
first_image.asnumpy())
- assert first_batch_roll_over_twice.pad == 1
- # we've called next once
- i = 1
- for _ in test_iter:
- i += 1
- # test the third epoch with size 6
- assert i == 6
- # test shuffle option for sanity test
- test_iter = mx.image.ImageIter(3, (3, 224, 224),
label_width=1, imglist=imglist, shuffle=True,
- path_imglist=path_imglist,
path_root='', dtype=dtype, last_batch_handle='pad')
- for _ in test_iter:
- pass
-
- for dtype in ['int32', 'float32', 'int64', 'float64']:
- check_imageiter(dtype)
-
- # test with default dtype
- check_imageiter()
+ imageiter_list = [
+ mx.image.ImageIter(2, (3, 224, 224), label_width=1,
imglist=imglist,
+ path_imglist=path_imglist, path_root='', dtype=dtype),
+ mx.image.ImageIter(3, (3, 224, 224), label_width=1,
imglist=imglist,
+ path_imglist=path_imglist, path_root='', dtype=dtype,
last_batch_handle='discard'),
+ mx.image.ImageIter(3, (3, 224, 224), label_width=1,
imglist=imglist,
+ path_imglist=path_imglist, path_root='', dtype=dtype,
last_batch_handle='pad'),
+ mx.image.ImageIter(3, (3, 224, 224), label_width=1,
imglist=imglist,
+ path_imglist=path_imglist, path_root='', dtype=dtype,
last_batch_handle='roll_over'),
+ mx.image.ImageIter(3, (3, 224, 224), label_width=1,
imglist=imglist, shuffle=True,
+ path_imglist=path_imglist, path_root='', dtype=dtype,
last_batch_handle='pad')
+ ]
+ _test_imageiter_last_batch(imageiter_list, (2, 3, 224, 224))
@with_seed()
def test_augmenters(self):
@@ -259,16 +262,20 @@ def test_image_detiter(self):
im_list = [_generate_objects() + [x] for x in TestImage.IMAGES]
det_iter = mx.image.ImageDetIter(2, (3, 300, 300), imglist=im_list,
path_root='')
for _ in range(3):
- for batch in det_iter:
+ for _ in det_iter:
pass
- det_iter.reset()
-
+ det_iter.reset()
val_iter = mx.image.ImageDetIter(2, (3, 300, 300), imglist=im_list,
path_root='')
det_iter = val_iter.sync_label_shape(det_iter)
assert det_iter.data_shape == val_iter.data_shape
assert det_iter.label_shape == val_iter.label_shape
- # test file list
+ # test batch_size is not divisible by number of images
+ det_iter = mx.image.ImageDetIter(4, (3, 300, 300), imglist=im_list,
path_root='')
+ for _ in det_iter:
+ pass
+
+ # test file list with last batch handle
fname = './data/test_imagedetiter.lst'
im_list = [[k] + _generate_objects() + [x] for k, x in
enumerate(TestImage.IMAGES)]
with open(fname, 'w') as f:
@@ -276,10 +283,19 @@ def test_image_detiter(self):
line = '\t'.join([str(k) for k in line])
f.write(line + '\n')
- det_iter = mx.image.ImageDetIter(2, (3, 400, 400), path_imglist=fname,
- path_root='')
- for batch in det_iter:
- pass
+ imageiter_list = [
+ mx.image.ImageDetIter(2, (3, 400, 400),
+ path_imglist=fname, path_root=''),
+ mx.image.ImageDetIter(3, (3, 400, 400),
+ path_imglist=fname, path_root='', last_batch_handle='discard'),
+ mx.image.ImageDetIter(3, (3, 400, 400),
+ path_imglist=fname, path_root='', last_batch_handle='pad'),
+ mx.image.ImageDetIter(3, (3, 400, 400),
+ path_imglist=fname, path_root='',
last_batch_handle='roll_over'),
+ mx.image.ImageDetIter(3, (3, 400, 400), shuffle=True,
+ path_imglist=fname, path_root='', last_batch_handle='pad')
+ ]
+ _test_imageiter_last_batch(imageiter_list, (2, 3, 400, 400))
def test_det_augmenters(self):
# only test if all augmenters will work
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