[BUG] - Metrics not working with Tensor inputs

[carreremax]

Subject
Metrics

Describe the bug
The metrics inheriting from CausalFidelity (like Deletion for example) do not work with EagerTensor.

Screenshots

...
File ***\venv\lib\site-packages\xplique\metrics\fidelity.py:179, in CausalFidelity.__init__(self, model, inputs, targets, batch_size, causal_mode, baseline_mode, steps, max_percentage_perturbed)
    176 self.baseline_mode = baseline_mode
    178 self.nb_features = np.prod(inputs.shape[1:-1])
--> 179 self.inputs_flatten = inputs.reshape((len(inputs), self.nb_features, inputs.shape[-1]))
    181 assert 0.0 < max_percentage_perturbed <= 1.0, "`max_percentage_perturbed` must be" \
    182                                               "in ]0, 1]."
    183 self.max_nb_perturbed = tf.math.floor(self.nb_features * max_percentage_perturbed)

File ***\venv\lib\site-packages\tensorflow\python\framework\ops.py:437, in Tensor.__getattr__(self, name)
    433 def __getattr__(self, name):
    434   if name in {"T", "astype", "ravel", "transpose", "reshape", "clip", "size",
    435               "tolist", "data"}:
    436     # TODO(wangpeng): Export the enable_numpy_behavior knob
--> 437     raise AttributeError(
    438         f"{type(self).__name__} object has no attribute '{name}'. " + """
    439       If you are looking for numpy-related methods, please run the following:
    440       from tensorflow.python.ops.numpy_ops import np_config
    441       np_config.enable_numpy_behavior()
    442     """)
    443   self.__getattribute__(name)

AttributeError: EagerTensor object has no attribute 'reshape'. 
        If you are looking for numpy-related methods, please run the following:
        from tensorflow.python.ops.numpy_ops import np_config
        np_config.enable_numpy_behavior()

To Reproduce
Minimal example :

import tensorflow as tf
from xplique.metrics import Deletion
import numpy as np

inputs = tf.convert_to_tensor(np.zeros((1,10,10,3)))
targets= tf.convert_to_tensor([1])
model = tf.keras.Model()
Deletion(None, inputs, targets)

Expected behavior
According to the documentation, inputs provided as tensor should work :

inputs: Union[tf.data.Dataset, tf.Tensor, np.ndarray],

Additional context
In my code, it works with a numpy array, but will stop working if i convert the inputs to a tensorflow Tensor of same shape and content.