40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
"""
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Copyright 2017-2018 Fizyr (https://fizyr.com)
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import keras
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import numpy as np
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import math
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class PriorProbability(keras.initializers.Initializer):
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""" Apply a prior probability to the weights.
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"""
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def __init__(self, probability=0.01):
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self.probability = probability
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def get_config(self):
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return {
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'probability': self.probability
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}
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def __call__(self, shape, dtype=None):
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# set bias to -log((1 - p)/p) for foreground
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result = np.ones(shape, dtype=dtype) * -math.log((1 - self.probability) / self.probability)
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return result
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