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tf.dtypes.cast

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Casts a tensor to a new type.

Aliases:

tf.dtypes.cast(
    x,
    dtype,
    name=None
)

Used in the guide:

Used in the tutorials:

The operation casts x (in case of Tensor) or x.values (in case of SparseTensor or IndexedSlices) to dtype.

For example:

x = tf.constant([1.8, 2.2], dtype=tf.float32)
tf.dtypes.cast(x, tf.int32)  # [1, 2], dtype=tf.int32

The operation supports data types (for x and dtype) of uint8, uint16, uint32, uint64, int8, int16, int32, int64, float16, float32, float64, complex64, complex128, bfloat16. In case of casting from complex types (complex64, complex128) to real types, only the real part of x is returned. In case of casting from real types to complex types (complex64, complex128), the imaginary part of the returned value is set to 0. The handling of complex types here matches the behavior of numpy.

Args:

  • x: A Tensor or SparseTensor or IndexedSlices of numeric type. It could be uint8, uint16, uint32, uint64, int8, int16, int32, int64, float16, float32, float64, complex64, complex128, bfloat16.
  • dtype: The destination type. The list of supported dtypes is the same as x.
  • name: A name for the operation (optional).

Returns:

A Tensor or SparseTensor or IndexedSlices with same shape as x and same type as dtype.

Raises:

  • TypeError: If x cannot be cast to the dtype.