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import tensorflow as tf
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import numpy as np
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def weight_variable_glorot(input_dim, output_dim, name=""):
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"""Create a weight variable with Glorot & Bengio (AISTATS 2010)
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initialization.
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"""
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init_range = np.sqrt(6.0 / (input_dim + output_dim))
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initial = tf.random_uniform([input_dim, output_dim], minval=-init_range,
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maxval=init_range, dtype=tf.float32)
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return tf.Variable(initial, name=name)
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