code: def _warn_on_suspicious_single_image_shape(image):
      if image is None:
          return
  
      # Check if it looks like (N, H, W) instead of (H, W, C).
      # We don't react to (1, 1, C) though, mostly because that is used in many
      # unittests.
      if (
          image.ndim == 3
          and image.shape[-1] >= 32
          and image.shape[0:2] != (1, 1)
      ):
          ia.warn(
              "You provided a numpy array of shape %s as a "
              "single-image augmentation input, which was interpreted as "
              "(H, W, C). The last dimension however has a size of >=32, "
              "which indicates that you provided a multi-image array "
              "with shape (N, H, W) instead. If that is the case, "
              "you should use e.g. augmenter(imageS=<your input>) or "
              "augment_imageS(<your input>). Otherwise your multi-image "
              "input will be interpreted as a single image during "
              "augmentation." % (image.shape,),
              category=SuspiciousSingleImageShapeWarning,
          )
  
file_path: imgaug/imgaug/augmenters/base.py
imports: from __future__ import print_function, division, absolute_import
  import imgaug
label_desc: Use image node_id 2 for calling a global function with example usage: _warn_on_suspicious_single_image_shape(image) without return types