tf.dtypes

TensorFlow 1 version

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Casts a tensor to a new type.

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Main aliases

tf.dtypes.cast

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.cast, tf.compat.v1.dtypes.cast

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

Used in the notebooks

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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)
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([1, 2], dtype=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.

Note casting nan and inf values to integral types has undefined behavior.

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`.

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tf.dtypes / Overview

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Used in the notebooks

For example:

Args

Returns

Raises