stu1130 commented on a change in pull request #12285: [WIP] Change the way
NDArrayIter handle the last batch
URL: https://github.com/apache/incubator-mxnet/pull/12285#discussion_r212142951
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File path: tests/python/unittest/test_io.py
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@@ -87,82 +87,68 @@ def test_Cifar10Rec():
for i in range(10):
assert(labelcount[i] == 5000)
-
-def test_NDArrayIter():
+def _init_NDArrayIter_data():
data = np.ones([1000, 2, 2])
- label = np.ones([1000, 1])
+ labels = np.ones([1000, 1])
for i in range(1000):
data[i] = i / 100
- label[i] = i / 100
- dataiter = mx.io.NDArrayIter(
- data, label, 128, True, last_batch_handle='pad')
- batchidx = 0
- for batch in dataiter:
- batchidx += 1
- assert(batchidx == 8)
- dataiter = mx.io.NDArrayIter(
- data, label, 128, False, last_batch_handle='pad')
- batchidx = 0
- labelcount = [0 for i in range(10)]
- for batch in dataiter:
- label = batch.label[0].asnumpy().flatten()
- assert((batch.data[0].asnumpy()[:, 0, 0] == label).all())
- for i in range(label.shape[0]):
- labelcount[int(label[i])] += 1
+ labels[i] = i / 100
+ return data, labels
- for i in range(10):
- if i == 0:
- assert(labelcount[i] == 124)
- else:
- assert(labelcount[i] == 100)
+def _test_last_batch_handle(data, labels):
+ idx = 0
+ last_batch_handle_list = ['pad', 'discard' , 'roll_over']
+ labelcount_list = [(124, 100), (100, 96), (100, 96)]
+ batch_count_list = [8, 7, 7]
+
+ for idx in range(len(last_batch_handle_list)):
+ dataiter = mx.io.NDArrayIter(
+ data, labels, 128, False,
last_batch_handle=last_batch_handle_list[idx])
+ batch_count = 0
+ labelcount = [0 for i in range(10)]
+ for batch in dataiter:
+ label = batch.label[0].asnumpy().flatten()
+ assert((batch.data[0].asnumpy()[:, 0, 0] == label).all()),
last_batch_handle_list[idx]
+ for i in range(label.shape[0]):
+ labelcount[int(label[i])] += 1
+ batch_count += 1
+ # assert result
+ assert(labelcount[0] == labelcount_list[idx][0]),
last_batch_handle_list[idx]
+ assert(labelcount[8] == labelcount_list[idx][1]),
last_batch_handle_list[idx]
+
+ assert batch_count == batch_count_list[idx]
+ # shuffle equals True for sanity test
+ dataiter = mx.io.NDArrayIter(
+ data, labels, 128, True,
last_batch_handle=last_batch_handle_list[idx])
+ batch_count = 0
+ for _ in dataiter:
+ batch_count += 1
+ assert batch_count == batch_count_list[idx]
Review comment:
Thanks for bringing up this issue. As @sandeep-krishnamurthy suggested, I
would check if the data points are moved to the right positions based on index
array. Within shuffle's implementation, the index array would shuffle first and
then we get the data by their shuffled index.
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