tf.dtypes.DType

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Represents the type of the elements in a Tensor.

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()

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 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

is_compatible_with

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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__

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__eq__(
    other
)

Returns True iff this DType refers to the same type as other.

__ne__

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__ne__(
    other
)

Returns True iff self != other.