Type DType
Namespace tensorflow
Parent PythonObjectContainer
Interfaces IDType
Represents the type of the elements in a `Tensor`. 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.
Methods
Properties
- as_datatype_enum
- as_datatype_enum_dyn
- as_numpy_dtype
- as_numpy_dtype_dyn
- base_dtype
- base_dtype_dyn
- is_bool
- is_bool_dyn
- is_complex
- is_complex_dyn
- is_floating
- is_floating_dyn
- is_integer
- is_integer_dyn
- is_numpy_compatible
- is_numpy_compatible_dyn
- is_quantized
- is_quantized_dyn
- is_unsigned
- is_unsigned_dyn
- limits
- limits_dyn
- max
- max_dyn
- min
- min_dyn
- name
- name_dyn
- PythonObject
- real_dtype
- real_dtype_dyn
- size
- size_dyn