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libsvm_to_tfrecord.py
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libsvm_to_tfrecord.py
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import os
import numpy as np
import tensorflow as tf
def convert_tfrecords(input_filename, output_filename):
"""Concert the LibSVM contents to TFRecord.
Args:
input_filename: LibSVM filename.
output_filename: Desired TFRecord filename.
"""
print("Starting to convert {} to {}...".format(input_filename, output_filename))
writer = tf.python_io.TFRecordWriter(output_filename)
for line in open(input_filename, "r"):
data = line.split(" ")
label = float(data[0])
ids = []
values = []
for fea in data[1:]:
id, value = fea.split(":")
ids.append(int(id))
values.append(float(value))
# Write samples one by one
example = tf.train.Example(features=tf.train.Features(feature={
"label":
tf.train.Feature(float_list=tf.train.FloatList(value=[label])),
"ids":
tf.train.Feature(int64_list=tf.train.Int64List(value=ids)),
"values":
tf.train.Feature(float_list=tf.train.FloatList(value=values))
}))
writer.write(example.SerializeToString())
writer.close()
print("Successfully converted {} to {}!".format(input_filename, output_filename))
sess = tf.InteractiveSession()
convert_tfrecords("/path/to/libsvm/file/train.libsvm", "/path/to/tfrecord/file/train.tfrecords")
sess.close()