def construct_placeholders():
# Define placeholders
placeholders = {
'batch1' : tf.placeholder(tf.int32, shape=(None), name='batch1'),
'batch2' : tf.placeholder(tf.int32, shape=(None), name='batch2'),
# negative samples for all nodes in the batch
'neg_samples': tf.placeholder(tf.int32, shape=(None,),
name='neg_sample_size'),
'dropout': tf.placeholder_with_default(0., shape=(), name='dropout'),
'batch_size' : tf.placeholder(tf.int32, name='batch_size'),
}
return placeholders
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