tf.dtypes.cast

TensorFlow 1 version

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Represents the type of the elements in a Tensor.

View aliases

Main aliases

tf.DType

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.DType, tf.compat.v1.dtypes.DType

tf.dtypes.DType()

The following DType objects are defined:

tf.float16: 16-bit half-precision floating-point.
tf.float32: 32-bit single-precision floating-point.
tf.float64: 64-bit double-precision floating-point.
tf.bfloat16: 16-bit truncated floating-point.
tf.complex64: 64-bit single-precision complex.
tf.complex128: 128-bit double-precision complex.
tf.int8: 8-bit signed integer.
tf.uint8: 8-bit unsigned integer.
tf.uint16: 16-bit unsigned integer.
tf.uint32: 32-bit unsigned integer.
tf.uint64: 64-bit unsigned integer.
tf.int16: 16-bit signed integer.
tf.int32: 32-bit signed integer.
tf.int64: 64-bit signed integer.
tf.bool: Boolean.
tf.string: String.
tf.qint8: Quantized 8-bit signed integer.
tf.quint8: Quantized 8-bit unsigned integer.
tf.qint16: Quantized 16-bit signed integer.
tf.quint16: Quantized 16-bit unsigned integer.
tf.qint32: Quantized 32-bit signed integer.
tf.resource: Handle to a mutable resource.
tf.variant: Values of arbitrary types.

The tf.as_dtype() function converts numpy types and string type names to a DType object.

Attributes
`as_datatype_enum`	Returns a `types_pb2.DataType` enum value based on this data type.
`as_numpy_dtype`	Returns a Python `type` object based on this `DType`.
`base_dtype`	Returns a non-reference `DType` based on this `DType`.
`is_bool`	Returns whether this is a boolean data type.
`is_complex`	Returns whether this is a complex floating point type.
`is_floating`	Returns whether this is a (non-quantized, real) floating point type.
`is_integer`	Returns whether this is a (non-quantized) integer type.
`is_numpy_compatible`	Returns whether this data type has a compatible NumPy data type.
`is_quantized`	Returns whether this is a quantized data type.
`is_unsigned`	Returns whether this type is unsigned. Non-numeric, unordered, and quantized types are not considered unsigned, and this function returns `False`.
`limits`	Return intensity limits, i.e. (min, max) tuple, of the dtype. Args: clip_negative : bool, optional If True, clip the negative range (i.e. return 0 for min intensity) even if the image dtype allows negative values. Returns min, max : tuple Lower and upper intensity limits.
`max`	Returns the maximum representable value in this data type.
`min`	Returns the minimum representable value in this data type.
`name`
`real_dtype`	Returns the `DType` corresponding to this `DType`'s real part.
`size`

Methods

`is_compatible_with`

View source

is_compatible_with(
    other
)

Returns True if the other DType will be converted to this DType.

The conversion rules are as follows:

DType(T)       .is_compatible_with(DType(T))        == True

Args
`other`	A `DType` (or object that may be converted to a `DType`).

Returns
True if a Tensor of the `other` `DType` will be implicitly converted to this `DType`.

`eq`

View source

__eq__(
    other
)

Returns True iff this DType refers to the same type as other.

`ne`

View source

__ne__(
    other
)

Returns True iff self != other.

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tf.dtypes / cast

View aliases

Attributes

Methods

is_compatible_with

__eq__

__ne__

`is_compatible_with`

`eq`

`ne`