tf.dtypes.DType

Represents the type of the elements in a Tensor.

Inherits From: TraceType

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()

DType's are used to specify the output data type for operations which require it, or to inspect the data type of existing Tensor's.

Examples:

tf.constant(1, dtype=tf.int64)
<tf.Tensor: shape=(), dtype=int64, numpy=1>
tf.constant(1.0).dtype
tf.float32

See tf.dtypes for a complete list of DType's defined.

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

experimental_as_proto

View source

experimental_as_proto() -> types_pb2.SerializedDType

Returns a proto representation of the Dtype instance.

experimental_from_proto

View source

@classmethod
experimental_from_proto(
    proto: types_pb2.SerializedDType
) -> 'DType'

Returns a Dtype instance based on the serialized proto.

experimental_type_proto

View source

@classmethod
experimental_type_proto() -> Type[types_pb2.SerializedDType]

Returns the type of proto associated with DType serialization.

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.

is_subtype_of

View source

is_subtype_of(
    other: tf.types.experimental.TraceType
) -> bool

See tf.types.experimental.TraceType base class.

most_specific_common_supertype

View source

most_specific_common_supertype(
    types: Sequence[tf.types.experimental.TraceType]
) -> Optional['DType']

See tf.types.experimental.TraceType base class.

__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.