can i train faster-rcnn-inception-v2 on multiple tfrecords?

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System information

• What is the top-level directory of the model you are using: /models/research/object_detection

• Have I written custom code (as opposed to using a stock example script provided in TensorFlow): used my own dataset

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 16.04

• TensorFlow installed from (source or binary): pip install

• TensorFlow version (use command below): 1.7.0

• Bazel version (if compiling from source):

• CUDA/cuDNN version:

• GPU model and memory: NVIDIA GeForce GTX 1080

• Exact command to reproduce: python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config

Describe the problem

I am trying to train a model on my own dataset. in tutorials that i had seen they always use one tfrecord for train and one for test - each containing data on multiple tagged images.
my data contains one tfrecord for each labeled image.
I tried to train the model on my tfrecords but it was not able to make the training.
is it possible to train on multiple tfrecords? if yes, how are they supposed to be arranged ?