TensorFlow record files are corrupted

I'm trying to train an FFN, and the first 2 steps (partition and build the coordinate file) seem to go fine, but training throws Key Value errors. On further inspection (using [TFRecord Viewer](https://github.com/sulc/tfrecord-viewer)), I get this error:
`tensorflow.python.framework.errors_impl.DataLossError: corrupted record at 0`.

Any help would be super appreciated!

TF version 1.13.2, and here are the exact calls I'm making:

For computing partitions:
`
python ../../ffn/compute_partitions.py \
--input_volume ../training_data_img.h5:label \
--output_volume training_data2.h5:af \
--thresholds 0.025,0.05,0.075,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9 \
--lom_radius 3,3,3 \
--min_size 10000`

For building the TFRecord file:
`
python ../../ffn/build_coordinates.py \
--partition_volumes validation:training_data2.h5:af \
--coordinate_output tf_record_fileyw \
--margin 3,3,3`

and for training:
`
python ../../ffn/train.py \
--train_coords tf_record_fileyw \
--data_volumes validation1:../training_data_img.h5:image \
--label_volumes validation1:../training_data_img.h5:label \
--model_name convstack_3d.ConvStack3DFFNModel \
--model_args "{\"depth\": 2, \"fov_size\": [2, 2, 2], \"deltas\": [2, 2, 2]}" \
--image_mean 72 \
--image_stddev 33`