def _add_chi_term_sum(
self,
optimizer_ins
):
for ok, ov in optimizer_ins.items():
if isinstance(ov['o'], list):
# with tf.device('/cpu:0'):
# self._chi_contribution = tf.Print(
# self._chi_contribution,
# [self._chi_contribution],
# message="\n\n(ChiNoise._add_chi_term_sum)self._chi_contribution:\n"
# )
changed = list()
for o in ov['o']:
noise = self._get_noise(tf.shape(o))
noise = normalize(noise, o)
# with tf.device('/cpu:0'):
# noise = tf.Print(
# noise,
# [global_norm([noise])],
# message="\n\n(ChiNoise._add_chi_term_sum)noise:\n"
# )
# o = tf.Print(
# o,
# [global_norm([o])],
# message="\n\n(ChiNoise._add_chi_term_sum)o:\n"
# )
changed.append(o + self._chi_contribution * noise)
ov['o'] = changed
# ov['o'] = [
# o + self._chi_contribution * self._get_noise(tf.shape(o))
# for o in ov['o']
# ]
else:
# with tf.device('/cpu:0'):
# self._chi_contribution = tf.Print(
# self._chi_contribution,
# [self._chi_contribution],
# message="\n\n(ChiNoise._add_chi_term_sum)self._chi_contribution:\n"
# )
noise = self._get_noise(tf.shape(ov['o']))
noise = normalize(noise, ov['o'])
# with tf.device('/cpu:0'):
# noise = tf.Print(
# noise,
# [global_norm([noise])],
# message="\n\n(ChiNoise._add_chi_term_sum)noise:\n"
# )
# ov['o'] = tf.Print(
# ov['o'],
#
# [global_norm([ov['o']])],
# message="\n\n(ChiNoise._add_chi_term_sum)ov['o']:\n"
# )
ov['o'] = ov['o'] + self._chi_contribution * noise
# ov['o'] = ov['o'] + self._chi_contribution * self._get_noise(tf.shape(ov['o']))
return optimizer_ins
def _add_chi_term_sum(self, optimizer_ins):
for ok, ov in optimizer_ins.items():
if isinstance(ov['o'], list):
ov['o'] = [
o + self._chi_contribution * normalize(theta, o)
for o, theta in zip(ov['o'], ov['theta'])
]
else:
ov['o'] = ov['o'] + self._chi_contribution * normalize(
ov['theta'], ov['o'])
return optimizer_ins