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tflite_support.task.processor.EmbeddingOptions
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Options for embedding processor.
tflite_support . task . processor . EmbeddingOptions (
l2_normalize : Optional [ bool ] = None , quantize : Optional [ bool ] = None
)
Attributes
l2_normalize
Whether to normalize the returned feature vector with L2 norm.
Use this option only if the model does not already contain a native
L2_NORMALIZATION TF Lite Op. In most cases, this is already the case and
L2 norm is thus achieved through TF Lite inference.
quantize
Whether the returned embedding should be quantized to bytes via
scalar quantization. Embeddings are implicitly assumed to be unit-norm and
therefore any dimension is guaranteed to have a value in [-1.0, 1.0]. Use
the l2_normalize option if this is not the case.
Methods
create_from_pb2
View source
@classmethod
create_from_pb2 (
pb2_obj : _EmbeddingOptionsProto
) -> 'EmbeddingOptions'
Creates a EmbeddingOptions
object from the given protobuf object.
to_pb2
View source
to_pb2 () -> _EmbeddingOptionsProto
Generates a protobuf object to pass to the C++ layer.
__eq__
View source
__eq__ (
other : Any
) -> bool
Checks if this object is equal to the given object.
Args
other
The object to be compared with.
Returns
True if the objects are equal.
Class Variables
l2_normalize
None
quantize
None
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Last updated 2024-05-08 UTC.
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{"lastModified": "Last updated 2024-05-08 UTC."}
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