class_docstr: A layer which asserts it's inputs are a certain type.
class_docstr_tok: ["A","layer","which","asserts","it","'s","inputs","are","a","certain","type","."]
docstr: Asserts `inputs` are of the correct type. Should be called in call().
docstr_tok: ["Asserts","`","inputs","`","are","of","the","correct","type",".","Should","be","called","in","call","(",")","."]
code: def assert_input_types(self, inputs):
      """Asserts `inputs` are of the correct type. Should be called in call()."""
      if self._assert_type:
          inputs_flattened = nest.flatten(inputs)
          for inp in inputs_flattened:
              assert inp.dtype.base_dtype == self._assert_type, (
                  "Input tensor has type %s which does not match assert type %s"
                  % (inp.dtype.name, self._assert_type)
              )
  
imports: from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_conversion
  from tensorflow.python.keras import regularizers
  from tensorflow.python.keras.engine import base_layer
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import custom_gradient
  from tensorflow.python.ops import math_ops
  from tensorflow.python.util import nest
label_desc: Use image node_id 2 for calling the AssertTypeLayer obj's underlying member method code with example usage: obj.assert_input_types(inputs) without return types