apeforest commented on a change in pull request #13557: Fix BatchNorm converter
for CoreML when fix_gamma=True
URL: https://github.com/apache/incubator-mxnet/pull/13557#discussion_r248155089
##########
File path: tools/coreml/test/test_mxnet_converter.py
##########
@@ -938,6 +938,40 @@ def test_batch_norm_no_global_stats(self):
name='batch_norm_1')
self._test_mxnet_model(net, input_shape=input_shape, mode='random',
delta=1e-2)
+ def test_batch_norm_with_fix_gamma(self):
+ """ The gamma will always be an array of ones when fix_gamma=True. The
values
+ of gamma may be changed accidentally if there have been
fix_gamma=False before
+ the final trained model.
+ """
+ np.random.seed(1988)
+ input_shape = (1, 2, 2, 3)
Review comment:
Why not use (1, 1, 2, 3) as in previous `test_batch_norm()` tests? I think
it can be helpful to choose the same input_shape to test the default behavior
when fix_gamma is not specified. Ideally, the result should be the same as you
supply fix_gamma=True.
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