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import numpy as np
import tensorflow as tf
def min_max_norm(img: np.ndarray, out_max_val=1.):
out_img = img
max_val = np.amax(img)
min_val = np.amin(img)
if (max_val - min_val) != 0:
out_img = (img - min_val) / (max_val - min_val)
return out_img * out_max_val
def soft_threshold(x, threshold, name=None):
# https://www.tensorflow.org/probability/api_docs/python/tfp/math/soft_threshold
with tf.name_scope(name or 'soft_threshold'):
x = tf.convert_to_tensor(x, name='x')
threshold = tf.convert_to_tensor(threshold, dtype=x.dtype, name='threshold')
return tf.sign(x) * tf.maximum(tf.abs(x) - threshold, 0.)
def binary_activation(x):
# https://stackoverflow.com/questions/37743574/hard-limiting-threshold-activation-function-in-tensorflow
cond = tf.less(x, tf.zeros(tf.shape(x)))
out = tf.where(cond, tf.zeros(tf.shape(x)), tf.ones(tf.shape(x)))
return out
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