TensorFlow 2 version | View source on GitHub |
Represents the type of the elements in a Tensor
.
tf.dtypes.DType(
type_enum
)
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.
Args | |
---|---|
type_enum
|
A types_pb2.DataType enum value.
|
Raises | |
---|---|
TypeError
|
If type_enum is not a value types_pb2.DataType .
|
Attributes | |
---|---|
as_datatype_enum
|
Returns a types_pb2.DataType enum value based on this DType .
|
as_numpy_dtype
|
Returns a numpy.dtype 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
|
|
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 |
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
|
Returns the string name for this DType .
|
real_dtype
|
Returns the dtype correspond to this dtype's real part. |
size
|
Methods
is_compatible_with
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__
__eq__(
other
)
Returns True iff this DType refers to the same type as other
.
__ne__
__ne__(
other
)
Returns True iff self != other.