Simple helper library to convert a collection of numpy data to tfrecord, and build a tensorflow dataset from the tfrecord.


$ git clone [email protected]:yonetaniryo/numpy2tfrecord.git
$ cd numpy2tfrecord
$ pip install .


$ pytest -v 

How to use

Convert a collection of numpy data to tfrecord

import numpy as np
from numpy2tfrecord import Numpy2Tfrecord

converter = Numpy2Tfrecord()
x = np.arange(100).reshape(10, 10).astype(np.float32)  # float array
y = np.arange(100).reshape(10, 10).astype(np.int64)  # int array
a = 5  # int
b = 0.3  # float
entry = {"x": x, "y": y, "a": a, "b": b}
converter.add(entry)  # add data entry

converter.export_to_tfrecord("test.tfrecord")  # export to tfrecord

Build a tensorflow dataset from tfrecord

dataset = build_dataset_from_tfrecord("test.tfrecord")  # load tfrecord and build


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