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* Use He initialization trick

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This commit is contained in:
Matthew Honnibal 2015-06-29 10:56:02 +02:00
parent 894cbef8ba
commit ca30fe1582
1 changed files with 3 additions and 5 deletions
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8
bin/parser/nn_train.py
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@ -77,14 +77,12 @@ def relu(x):
def _init_weights(n_in, n_out):
rng = numpy.random.RandomState(1234)
weights = numpy.asarray(
numpy.random.normal(
loc=0.0,
scale=0.0001,
size=(n_in, n_out)),
rng.standard_normal(size=(n_in, n_out)) * numpy.sqrt(2.0 / n_in),
dtype=theano.config.floatX
)
bias = 0.2 * numpy.ones((n_out,), dtype=theano.config.floatX)
bias = numpy.zeros((n_out,), dtype=theano.config.floatX)
return [AvgParam(weights, name='W'), AvgParam(bias, name='b')]