Comments (1)
parthvadhadiya
commented on May 29, 2024
solution
with tf.variable_scope(tf.get_variable_scope(),reuse=False):
d_trainer_real = tf.train.AdamOptimizer(0.0003).minimize(d_loss_real, var_list=d_vars)
d_trainer_fake = tf.train.AdamOptimizer(0.0003).minimize(d_loss_fake, var_list=d_vars)
g_trainer = tf.train.AdamOptimizer(0.0001).minimize(g_loss, var_list=g_vars)
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Related Issues (8)
- Error for running with TensorFlow: ValueError: Variable d_w1/Adam/ does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=None in VarScope? HOT 5
- Python 3.5 TensorFlow 1.2 variable scope related error HOT 2
- What should I do if I want to use this to train my own database HOT 2
- Training Betas and Gammas of the batch normalization HOT 3
- Not able to load pre-trained model HOT 4
- ValueError: Variable d_w1/Adam_5/ does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=tf.AUTO_REUSE in VarScope? HOT 3
- why this code only in discriminator, but not in generator?: HOT 1
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