tf.dtypes.DType
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.
© 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/r1.15/api_docs/python/tf/dtypes/DType