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CVAEutils.py
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CVAEutils.py
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import tensorflow as tf
initializer = tf.contrib.layers.variance_scaling_initializer(factor = 1.0)
def conv(inputs,filters,name):
net = tf.layers.conv2d(inputs = inputs,
filters = filters,
kernel_size = [3,3],
strides = (1,1),
padding ="SAME",
kernel_initializer = initializer,
name = name,
reuse = tf.AUTO_REUSE)
return net
def maxpool(input,name):
net = tf.nn.max_pool(value = input, ksize = [1,2,2,1], strides = [1,2,2,1], padding = "SAME", name = name)
return net
def bn(inputs,is_training,name):
net = tf.contrib.layers.batch_norm(inputs, decay = 0.9, is_training = is_training, reuse = tf.AUTO_REUSE, scope = name)
return net
def leaky(input):
return tf.nn.leaky_relu(input)
def drop_out(input, keep_prob):
return tf.nn.dropout(input, rate=1-keep_prob)
def dense(inputs, units, name):
net = tf.layers.dense(inputs = inputs,
units = units,
reuse = tf.compat.v1.AUTO_REUSE,
name = name,
kernel_initializer = initializer)
return net