[GitHub] [incubator-mxnet] guanxinq commented on a change in pull request #17242: add RandomApply in gluon's transforms

[GitBox <gi...@apache.org>]

guanxinq commented on a change in pull request #17242: add RandomApply in gluon's transforms
URL: https://github.com/apache/incubator-mxnet/pull/17242#discussion_r363952366
 
 

 ##########
 File path: tests/python/unittest/test_gluon_data_vision.py
 ##########
 @@ -229,6 +229,21 @@ def test_transformer():
     transform(mx.nd.ones((245, 480, 3), dtype='uint8')).wait_to_read()
 
 
+@with_seed()
+def test_randomtransforms():
+    from mxnet.gluon.data.vision import transforms
+
+    transform = transforms.Compose([transforms.RandomApply(transforms.Compose([transforms.Resize(300), transforms.RandomResizedCrop(224)]), 0.5)])
+    
+    img = mx.nd.ones((245, 480, 3), dtype='uint8')
+    iteration = 1000
+    num_apply = 0
+    for i in range(iteration):
+        out = transform(img)
+        if out.shape[0] == 224:
+            num_apply += 1
+    assert(abs(num_apply/float(iteration)-0.5) < 1e-1)
 
 Review comment:
   Sure. Did not notice that threshold could be passed into assert_almost_equal().

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