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Removed duplicate loss log

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Signed-off-by: Jim Martens <github@2martens.de>
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Jim Martens
2019-04-15 10:24:16 +02:00
parent 3afb74587b
commit 1243cc0a4b
1 changed files with 0 additions and 3 deletions
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src/twomartens/masterthesis/aae/train.py
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@ -210,15 +210,12 @@ def _train_enc_dec_step_simple(encoder: model.Encoder, decoder: model.Decoder,
x_decoded = decoder(z) x_decoded = decoder(z)
reconstruction_loss = tf.losses.log_loss(inputs, x_decoded) reconstruction_loss = tf.losses.log_loss(inputs, x_decoded)
_enc_dec_train_loss = reconstruction_loss
enc_dec_grads = tape.gradient(_enc_dec_train_loss, enc_dec_grads = tape.gradient(_enc_dec_train_loss,
encoder.trainable_variables + decoder.trainable_variables) encoder.trainable_variables + decoder.trainable_variables)
if int(global_step % LOG_FREQUENCY) == 0: if int(global_step % LOG_FREQUENCY) == 0:
summary_ops_v2.scalar(name='reconstruction_loss', tensor=reconstruction_loss, summary_ops_v2.scalar(name='reconstruction_loss', tensor=reconstruction_loss,
step=global_step) step=global_step)
summary_ops_v2.scalar(name='encoder_decoder_loss', tensor=_enc_dec_train_loss,
step=global_step)
for grad, variable in zip(enc_dec_grads, encoder.trainable_variables + decoder.trainable_variables): for grad, variable in zip(enc_dec_grads, encoder.trainable_variables + decoder.trainable_variables):
summary_ops_v2.histogram(name='gradients/' + variable.name, tensor=tf.math.l2_normalize(grad), summary_ops_v2.histogram(name='gradients/' + variable.name, tensor=tf.math.l2_normalize(grad),
step=global_step) step=global_step)