/TensorFlow 2.3


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Represents the type of the elements in a Tensor.

The following DType objects are defined:

The tf.as_dtype() function converts numpy types and string type names to a DType object.

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.
real_dtype Returns the DType corresponding to this DType's real part.



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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
other A DType (or object that may be converted to a DType).
True if a Tensor of the other DType will be implicitly converted to this DType.


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


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Returns True iff self != other.

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.