View source on GitHub |
Represents the type of the elements in a Tensor
.
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 |
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 |
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.
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/dtypes/DType