Running object detection with: Tensorflow/models/research/object_detection/model_main_tf2.py stops after 2000 steps when there are more than 2000 .jpg files

Prerequisites

Please answer the following questions for yourself before submitting an issue.

• [ Yes] I am using the latest TensorFlow Model Garden release and TensorFlow 2.
• [ YEs] I am reporting the issue to the correct repository. (Model Garden official or research directory)
• I checked to make sure that this issue has not been filed already.

1. The entire URL of the file you are using

https://github.com/tensorflow/models/tree/master/official/...

2. Describe the bug

Based on model "ssd_mobilenet_v1_fpn_640x640_coco17_tpu-8", there are 2000 .jpg files and 2000.xml files, it's converted to tfrecord file with generate_tfrecord.py.
Then run command:

python Tensorflow/models/research/object_detection/model_main_tf2.py --model_dir=Tensorflow/workspace6Objects/models/my_ssd_mobnet_ssd_mobilenet_v1_fpn_640x640_coco17_tpu-8_6Objects_GPU --pipeline_config_path=Tensorflow/workspace6Objects/models/my_ssd_mobnet_ssd_mobilenet_v1_fpn_640x640_coco17_tpu-8_6Objects_GPU/pipeline.config --num_train_steps=10000

It runs up to 1000 steps, then finish. it should run up to 10000 steps.
There is no any error.

It works fine if the number .jpg files is 1500 or below.

Why is it not working for samples more than 2000?

Please help.

3. Steps to reproduce

Steps to reproduce the behavior.

4. Expected behavior

It should finish all the steps --num_train_steps=10000

5. Additional context

Include any logs that would be helpful to diagnose the problem.

6. System information

• OS Platform and Distribution: Linux Ubuntu 20.04):
• TensorFlow installed from binary):
• TensorFlow version (use command below): 2.8.0
• Python version: 3.8.10
• • Bazel version (if compiling from source):
• GCC/Compiler version (if compiling from source):
• CUDA/cuDNN version:
• GPU model and memory: