stu1130 commented on a change in pull request #13614: Make to_tensor and
normalize to accept 3D or 4D tensor inputs
URL: https://github.com/apache/incubator-mxnet/pull/13614#discussion_r240800204
##########
File path: tests/python/unittest/test_gluon_data_vision.py
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@@ -19,30 +19,66 @@
import mxnet.ndarray as nd
import numpy as np
from mxnet import gluon
+from mxnet.base import MXNetError
from mxnet.gluon.data.vision import transforms
from mxnet.test_utils import assert_almost_equal
from mxnet.test_utils import almost_equal
-from common import setup_module, with_seed, teardown
-
+from common import assertRaises, setup_module, with_seed, teardown
@with_seed()
def test_to_tensor():
+ # 3D Input
data_in = np.random.uniform(0, 255, (300, 300, 3)).astype(dtype=np.uint8)
Review comment:
```suggestion
data_in = nd.random.uniform(0, 255, (300, 300, 3)).astype(dtype=np.uint8)
```
directly initialize ndarray would be better?
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