You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
The first stage training is very effective, but when I want to test the accuracy, some issues turned out:
in the model.py anomaly_detector() self.ano_y = none. it will report an error in the def _sampler:
yb = tf.reshape(y, [-1, 1, 1, self.y_dim]),because none cannot be reshaped.
2.and when test, the batch_size is set to 1, the self.batch_size in _sampler should also be set to 1.
3.After I modify these codes, and change the input from images into the same data with train, the samples are just like some noises, and I wonder why.
The text was updated successfully, but these errors were encountered:
@lzzlxxlsz I tested the images and no, the generated images seem to be noise and the other image is most likely the gray scale image of the test image.
The first stage training is very effective, but when I want to test the accuracy, some issues turned out:
yb = tf.reshape(y, [-1, 1, 1, self.y_dim]),because none cannot be reshaped.
2.and when test, the batch_size is set to 1, the self.batch_size in _sampler should also be set to 1.
3.After I modify these codes, and change the input from images into the same data with train, the samples are just like some noises, and I wonder why.
The text was updated successfully, but these errors were encountered: