The batch_size problem with tf 2.4 is the result of a change in the huber loss function:
https://github.com/tensorflow/tensorflow/blob/v2.4.0/tensorflow/python/keras/losses.py#L1426
https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/keras/losses.py#L885

tf2.0:

tf.losses.Huber(reduction=tf.losses.Reduction.NONE)(tf.ones(shape=(2,16500,4)),tf.ones(shape=(2,16500,4))).shape
TensorShape([2, 16500, 4])

tf 2.4:

tf.losses.Huber(reduction=tf.losses.Reduction.NONE)(tf.ones(shape=(2,16500,4)),tf.ones(shape=(2,16500,4))).shape
TensorShape([2, 16500])

Fixing the bug for tf 2.4 is easy: Remove the additional reduce_sum in the reg_loss in line 218.
https://github.com/FurkanOM/tf-faster-rcnn/blob/master/utils/train_utils.py#L218

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Are you doing this without modifying anything or are you trying to implement your own code?

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without modifying anything

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Probably tf version mismatch, try tf 2.0 not others.

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my tf version is 2.3.1 is that mismatch and i am working with cpu not gpu??

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i tried on tf2.0 it was aproblems on tensorflow datasets like this :
google.protobuf.json_format.ParseError: Message type "tensorflow_datasets.DatasetInfo" has no field named "downloadSize".
Available Fields(except extensions): ['name', 'description', 'version', 'citation', 'sizeInBytes', 'location', 'downloadChecksums', 'schema', 'splits', 'supervisedKeys', 'redistributionInfo']

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what version of tfds is suitable?

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Hi,
Using a batch size of 1 I resolved with this issue. I'm looking to make it work with batch size > 1. I'll let you know if I figured out how to make it work for batch size > 1. I'm using tf 2.4.

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Anyone know with Tensorflow 2.8.0, seems the error now change to

ValueError: in user code:    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1021, in train_function  *        return step_function(self, iterator)    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1010, in step_function  **        outputs = model.distribute_strategy.run(run_step, args=(data,))    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1000, in run_step  **        outputs = model.train_step(data)    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 861, in train_step        self._validate_target_and_loss(y, loss)    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 819, in _validate_target_and_loss        'Target data is missing. Your model was compiled with '    ValueError: Target data is missing. Your model was compiled with loss=ListWrapper([None, None, None, None, None, None, None, None, None]), and therefore expects target data to be provided in 'fit()'

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Hi @ruman1609,
Try the solution I proposed in #17 by changing the format of inputs and targets. It seems you don't give target data to the fit function. Otherwise, downgrade your tf version.

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Hi @colindecourt I already do like you do, and like @wr0112358 did. Still the error occurred so right now I using 2.1.0 version. The error log was just like I sent before is using TF 2.8.0. That's why I downgrade my TF to 2.1.0

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