class_docstr: Describes a numpy array or scalar shape and dtype.
  
  An `ArraySpec` allows an API to describe the arrays that it accepts or
  returns, before that array exists.
  The equivalent version describing a `tf.Tensor` is `TensorSpec`.
docstr: Checks if the shape and dtype of two specs are equal.
docstr_tok: ["Checks","if","the","shape","and","dtype","of","two","specs","are","equal","."]
code: def __eq__(self, other):
      """Checks if the shape and dtype of two specs are equal."""
      if not isinstance(other, ArraySpec):
          return False
      return self.shape == other.shape and self.dtype == other.dtype
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numbers
  import gin
  import numpy
  import tensorflow
label_desc: Use image node_id 6 for calling the ArraySpec obj's underlying member method code with example usage: obj.__eq__(other) and returns: unknown, False