making tf custom layer with ragged tensor inputs to tensor outputs - tensorflow

Question

class CropLayer(layers.Layer):
def __init__(self, crop_t, **kwargs):
super().__init__(**kwargs)
self.crop_t = crop_t
def get_config(self):
config = super().get_config()
config.update({'crop_t': self.crop_t})
return config
def call(self, inputs):
outputs = []
for i, x in enumerate(inputs):
t = tf.shape(x[0])[0]
start = tf.experimental.numpy.random.randint(0, t-self.crop_t, dtype='int32')
end = start + self.crop_t
outputs.append(inputs[i, :, start:end].to_list())
return tf.constant(outputs)
def get_cropper(crop_t):
return keras.Sequential(
[
keras.Input(shape=(N, None), ragged=True),
CropLayer(crop_t)
]
)
cropper = get_cropper(crop_t)
I want to make a custom layer that the ragged tensor as input and tensor as output.
The layer crop ragged tensors to fit the size, so it can convert to tensor format. But when I run this code, the following error occurs.
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-96-6430b3383331> in <module>()
----> 1 cropperr = get_cropper(crop_t)
3 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py in wrapper(*args, **kwargs)
690 except Exception as e: # pylint:disable=broad-except
691 if hasattr(e, 'ag_error_metadata'):
--> 692 raise e.ag_error_metadata.to_exception(e)
693 else:
694 raise
ValueError: Exception encountered when calling layer "crop_layer_7" (type CropLayer).
in user code:
File "<ipython-input-93-419907fac9d0>", line 31, in call *
outputs.append(inputs[i, :, start:end].to_list())
ValueError: to_list can only be used in eager mode.