ValueError: Unexpectedly found an instance of type `<class 'keras.engine.keras_tensor.KerasTensor'>`. Expected a symbolic tensor instance.

[hmoghimifam]

Traceback (most recent call last): File "/home/wolverine/Documents/git/EfficientDet/inference.py", line 62, in <module> main() File "/home/wolverine/Documents/git/EfficientDet/inference.py", line 29, in main score_threshold=score_threshold) File "/home/wolverine/Documents/git/EfficientDet/model.py", line 430, in efficientdet features = backbone_cls(input_tensor=image_input, freeze_bn=freeze_bn) File "/home/wolverine/Documents/git/EfficientDet/utils/__init__.py", line 45, in wrapper return func(*args, **kwargs) File "/home/wolverine/Documents/git/EfficientDet/efficientnet.py", line 475, in EfficientNetB1 **kwargs) File "/home/wolverine/Documents/git/EfficientDet/efficientnet.py", line 382, in EfficientNet if not is_keras_tensor(input_tensor): File "/home/wolverine/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow/python/keras/backend.py", line 1282, in is_keras_tensor '. Expected a symbolic tensor instance.')
ValueError: Unexpectedly found an instance of type <class 'keras.engine.keras_tensor.KerasTensor'>. Expected a symbolic tensor instance.`

I keep getting the following error whether I try inference or training. I tried uncommenting import keras and import tensorflow parts but it didn't help. I'm using tensorflow 2.9.2

[YuraLi88]

The best way to solve the issue is to downgrade your TF version. Use the appropriate docker image for the environment isolation.
For example, TF 2.2.

[stale]

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

[AbhinavGopal]

With tf 2.2, the following error appears:

` /home/abhinavg/EfficientDet/layers.py:302 filter_detections *
ratios,
/home/abhinavg/EfficientDet/layers.py:197 filter_detections *
labels = c * tf.ones((keras.backend.shape(scores)[0],), dtype='int64')
/home/abhinavg/.local/lib/python3.7/site-packages/tensorflow/python/ops/array_ops.py:2967 ones **
output = _constant_if_small(one, shape, dtype, name)
/home/abhinavg/.local/lib/python3.7/site-packages/tensorflow/python/ops/array_ops.py:2662 _constant_if_small
if np.prod(shape) < 1000:
<array_function internals>:6 prod

/home/abhinavg/.local/lib/python3.7/site-packages/numpy/core/fromnumeric.py:3052 prod
    keepdims=keepdims, initial=initial, where=where)
/home/abhinavg/.local/lib/python3.7/site-packages/numpy/core/fromnumeric.py:86 _wrapreduction
    return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
/home/abhinavg/.local/lib/python3.7/site-packages/tensorflow/python/framework/ops.py:749 __array__
    " array.".format(self.name))

NotImplementedError: Cannot convert a symbolic Tensor (strided_slice_1:0) to a numpy array.`


I basically did a tf-gpu2.2 installation, then deleted the tf requirement from requirements.txt, and then did pip3 install -r requirements.txt