TensorFlow 1 version
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View source on GitHub
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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 | |
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type_enum
|
A types_pb2.DataType enum value.
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Raises | |
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TypeError
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If type_enum is not a value types_pb2.DataType.
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Attributes | |
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as_datatype_enum
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Returns a types_pb2.DataType enum value based on this DType.
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as_numpy_dtype
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Returns a numpy.dtype based on this DType.
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base_dtype
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Returns a non-reference DType based on this DType.
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is_bool
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Returns whether this is a boolean data type |
is_complex
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Returns whether this is a complex floating point type. |
is_floating
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Returns whether this is a (non-quantized, real) floating point type. |
is_integer
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Returns whether this is a (non-quantized) integer type. |
is_numpy_compatible
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is_quantized
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Returns whether this is a quantized data type. |
is_unsigned
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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
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Returns the minimum representable value in this data type. |
name
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Returns the string name for this DType.
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real_dtype
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Returns the dtype correspond to this dtype's real part. |
size
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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 | |
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other
|
A DType (or object that may be converted to a DType).
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| Returns | |
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True if a Tensor of the other DType will be implicitly converted to
this DType.
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__eq__
__eq__(
other
)
Returns True iff this DType refers to the same type as other.
__ne__
__ne__(
other
)
Returns True iff self != other.