tf.debugging.assert_type

Asserts that the given Tensor is of the specified type.

tf.debugging.assert_type(
    tensor, tf_type, message=None, name=None
)

This can always be checked statically, so this method returns nothing.

a = tf.Variable(1.0)
tf.debugging.assert_type(a, tf_type= tf.float32)

b = tf.constant(21)
tf.debugging.assert_type(b, tf_type=tf.bool)
Traceback (most recent call last):

TypeError: ...

c = tf.SparseTensor(indices=[[0, 0], [1, 2]], values=[1, 2],
 dense_shape=[3, 4])
tf.debugging.assert_type(c, tf_type= tf.int32)

Args
`tensor`	A `Tensor`, `SparseTensor` or `tf.Variable` .
`tf_type`	A tensorflow type (`dtypes.float32`, `tf.int64`, `dtypes.bool`, etc).
`message`	A string to prefix to the default message.
`name`	A name for this operation. Defaults to "assert_type"

Raises
`TypeError`	If the tensor's data type doesn't match `tf_type`.

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Last updated 2024-04-26 UTC.

Args