Colab script for object detection with tensorflow and keras – ValueError: Unexpected result of `train_function` (Empty logs)

Hello to everyone,

I am trying to adapt the script from this link keras example to my custom dataset but I run into the following issue:

‘ValueError: Unexpected result of train_function
(Empty logs). Please use Model.compile(…, run_eagerly=True)
, or tf.config.run_functions_eagerly(True)
for more information of where went wrong, or file a issue/bug to tf.keras
.

My dataset is (I flattened it in order to surpass error for converting dict to tensorflow)

<TensorSliceDataset element_spec={'image/filename': TensorSpec(shape=(), dtype=tf.string, name=None), 'image/id': TensorSpec(shape=(), dtype=tf.int32, name=None), 'is_crowd': TensorSpec(shape=(), dtype=tf.bool, name=None), 'area': TensorSpec(shape=(), dtype=tf.float32, name=None), 'bbox': TensorSpec(shape=(1, 4), dtype=tf.float32, name=None), 'id': TensorSpec(shape=(), dtype=tf.int32, name=None), 'image': TensorSpec(shape=(480, 640, 3), dtype=tf.float32, name=None), 'label': TensorSpec(shape=(), dtype=tf.int32, name=None)}> 

while the example dataset is

<PrefetchDataset element_spec={'image': TensorSpec(shape=(None, None, 3), dtype=tf.uint8, name=None), 'image/filename': TensorSpec(shape=(), dtype=tf.string, name=None), 'image/id': TensorSpec(shape=(), dtype=tf.int64, name=None), 'objects': {'area': TensorSpec(shape=(None,), dtype=tf.int64, name=None), 'bbox': TensorSpec(shape=(None, 4), dtype=tf.float32, name=None), 'id': TensorSpec(shape=(None,), dtype=tf.int64, name=None), 'is_crowd': TensorSpec(shape=(None,), dtype=tf.bool, name=None), 'label': TensorSpec(shape=(None,), dtype=tf.int64, name=None)}}> 

My script is publicly available here. If anyone can help with what I am doing wrong (i.e. input images, tensors, model building), I would be so grateful!!