modify dropoutnet in case of batch size mismatch #505
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� Conflicts: � easy_rec/version.py
� Conflicts: � docs/source/train.md
# Conflicts: # docs/source/component/custom_loss.md # easy_rec/python/loss/jrc_loss.py
eric-gecheng
reviewed
Dec 5, 2024
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Draw some random uniform numbers, then check them with keep_rate. Maybe it's simpler in this way to get bernoulli numbers?
mask = tf.random.uniform(shape=(20,)) < keep_rate
mask = tf.cast(mask, tf.int32)
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yeah! both do almost the same thing~
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I tested on higher version of tensorflow(2.18), below statement is not working, giving some error messages, maybe due to tf and numpy compatibility issue:
import tensorflow as tf
tf = tf.compat.v1
keep_rate = 0.2
dist = tf.distributions.Bernoulli(probs=keep_rate)
dist.sample(sample_shape=(5,))
error msg:
AttributeError: module 'numpy.core.multiarray' has no attribute 'integer'
poson
approved these changes
Dec 10, 2024
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