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Fix dumps for Constant initializer #15150

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Jul 19, 2019
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Fix dumps for Constant initializer #15150

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db81ea9
update dumps for const init
abhinavs95 Jun 4, 2019
d0db62c
add test
abhinavs95 Jun 6, 2019
0452c9c
fix for numpy input
abhinavs95 Jun 6, 2019
071a065
randomize test array shape and dim
abhinavs95 Jun 7, 2019
03b9983
fix test
abhinavs95 Jun 7, 2019
fe8828d
replace type with isinstance
abhinavs95 Jun 18, 2019
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5 changes: 5 additions & 0 deletions python/mxnet/initializer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -464,6 +464,11 @@ def __init__(self, value):
def _init_weight(self, _, arr):
arr[:] = self.value

def dumps(self):
if not np.isscalar(self._kwargs['value']):
self._kwargs['value'] = self._kwargs['value'].asnumpy().tolist()
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return json.dumps([self.__class__.__name__.lower(), self._kwargs])

@register
class Uniform(Initializer):
"""Initializes weights with random values uniformly sampled from a given range.
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11 changes: 10 additions & 1 deletion tests/python/unittest/test_init.py
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Expand Up @@ -67,10 +67,19 @@ def test_bilinear_init():
bili_1d = np.array([[1/float(4), 3/float(4), 3/float(4), 1/float(4)]])
bili_2d = bili_1d * np.transpose(bili_1d)
assert (bili_2d == bili_weight.asnumpy()).all()


def test_const_init_dumps():
# test NDArray input
init = mx.init.Constant(mx.nd.ones(5))
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it might be good if we could randomize the shape and dimension for this test and test it for different dimensions

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Added randomized shape and dimension for the array in test, it can take values between 1 and 10 with 1D to 5D shapes.

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@anirudhacharya anirudhacharya Jun 7, 2019 •
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in line 29 test_variable_init and other initializer tests are written differently. can we follow a similar pattern of declaring a sym variable and binding it to a module and initializing the params.

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I am just checking the function of dumps() in the test I have added, is creating a module still required? test_rsp_const_init in line 48 already does that for Constant initializers.

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test_rsp_const_init does the following -
https://github.com/apache/incubator-mxnet/blob/master/tests/python/unittest/test_init.py#L52-L57

The reason I am asking this change is because I think that will be a more comprehensive test and will check the whole flow, and it will test the initializer the way it will actually be used in production. This change should enable serializing and deserializing an ndarray object.

Just check once with a committer who will merge this code. Everything else LGTM.

assert init.dumps() == '["constant", {"value": [1.0, 1.0, 1.0, 1.0, 1.0]}]'
# test scalar input
init = mx.init.Constant(1)
assert init.dumps() == '["constant", {"value": 1}]'

if __name__ == '__main__':
test_variable_init()
test_default_init()
test_aux_init()
test_rsp_const_init()
test_bilinear_init()
test_const_init_dumps()