Is there any way to split .tfrecords file into many .tfrecords files directly, without writing back each Dataset example ?
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Answer
You can use a function like this:
import tensorflow as tf def split_tfrecord(tfrecord_path, split_size): with tf.Graph().as_default(), tf.Session() as sess: ds = tf.data.TFRecordDataset(tfrecord_path).batch(split_size) batch = ds.make_one_shot_iterator().get_next() part_num = 0 while True: try: records = sess.run(batch) part_path = tfrecord_path + '.{:03d}'.format(part_num) with tf.python_io.TFRecordWriter(part_path) as writer: for record in records: writer.write(record) part_num += 1 except tf.errors.OutOfRangeError: break
For example, to split the file my_records.tfrecord
into parts of 100 records each, you would do:
split_tfrecord(my_records.tfrecord, 100)
This would create multiple smaller record files my_records.tfrecord.000
, my_records.tfrecord.001
, etc.