Open jasstionzyf opened 4 years ago
as i read loss function, notice:
non_neg_mask = tf.fill(tf.shape(labels), -1.0, name='non_neg') non_neg_mask = tf.cast(tf.not_equal(labels, non_neg_mask), tf.float32) tf.summary.histogram('non_neg', non_neg_mask)
but based on above code , non_neg_mask is alwayes like : [1,1,1,1,1,1,1] wonder non_neg_mask is useless?
as i read loss function, notice:
b. get non-negative mask
non_neg_mask = tf.fill(tf.shape(labels), -1.0, name='non_neg') non_neg_mask = tf.cast(tf.not_equal(labels, non_neg_mask), tf.float32) tf.summary.histogram('non_neg', non_neg_mask)
but based on above code , non_neg_mask is alwayes like : [1,1,1,1,1,1,1] wonder non_neg_mask is useless?