From 1243cc0a4be84d77988493ff6f69e4f46ae368a7 Mon Sep 17 00:00:00 2001 From: Jim Martens Date: Mon, 15 Apr 2019 10:24:16 +0200 Subject: [PATCH] Removed duplicate loss log Signed-off-by: Jim Martens --- src/twomartens/masterthesis/aae/train.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/src/twomartens/masterthesis/aae/train.py b/src/twomartens/masterthesis/aae/train.py index 8dfbea1..94275db 100644 --- a/src/twomartens/masterthesis/aae/train.py +++ b/src/twomartens/masterthesis/aae/train.py @@ -210,15 +210,12 @@ def _train_enc_dec_step_simple(encoder: model.Encoder, decoder: model.Decoder, x_decoded = decoder(z) reconstruction_loss = tf.losses.log_loss(inputs, x_decoded) - _enc_dec_train_loss = reconstruction_loss enc_dec_grads = tape.gradient(_enc_dec_train_loss, encoder.trainable_variables + decoder.trainable_variables) if int(global_step % LOG_FREQUENCY) == 0: summary_ops_v2.scalar(name='reconstruction_loss', tensor=reconstruction_loss, 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): summary_ops_v2.histogram(name='gradients/' + variable.name, tensor=tf.math.l2_normalize(grad), step=global_step)