class_docstr: This attack was originally implemented by Goodfellow et al. (2015) with the infinity norm (and is known as the "Fast
  Gradient Sign Method"). This implementation extends the attack to other norms, and is therefore called the Fast
  Gradient Method.
  
  | Paper link: https://arxiv.org/abs/1412.6572
class_docstr_tok: ["This","attack","was","originally","implemented","by","Goodfellow","et","al",".","(","2015",")","with","the","infinity","norm","(","and","is","known","as","the","``","Fast","Gradient","Sign","Method","''",")",".","This","implementation","extends","the","attack","to","other","norms",",","and","is","therefore","called","the","Fast","Gradient","Method",".","|","Paper","link",":","https",":","\/\/arxiv.org\/abs\/1412.6572"]
docstr: Check the compatibility of the input with `eps` and `eps_step` which are of the same shape.
  
  :param x: An array with the original inputs.
docstr_tok: ["Check","the","compatibility","of","the","input","with","`","eps","`","and","`","eps_step","`","which","are","of","the","same","shape",".",":","param","x",":","An","array","with","the","original","inputs","."]
code: def _check_compatibility_input_and_eps(self, x: np.ndarray):
      """
      Check the compatibility of the input with `eps` and `eps_step` which are of the same shape.
  
      :param x: An array with the original inputs.
      """
      if isinstance(self.eps, np.ndarray):
          # Ensure the eps array is broadcastable
          if self.eps.ndim > x.ndim:  # pragma: no cover
              raise ValueError(
                  "The `eps` shape must be broadcastable to input shape."
              )
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import Optional, Union, TYPE_CHECKING
  import numpy
  from art.config import ART_NUMPY_DTYPE
  from art.attacks.attack import EvasionAttack
  from art.estimators.estimator import BaseEstimator, LossGradientsMixin
  from art.estimators.classification.classifier import ClassifierMixin
  from art.utils import compute_success, get_labels_np_array, random_sphere, projection, check_and_transform_label_format
  from art.summary_writer import SummaryWriter
label_desc: Use image node_id 2 for calling the FastGradientMethod obj's underlying member method code with example usage: obj._check_compatibility_input_and_eps(x) without return types