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

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@classmethod
create_from_pb2(
    pb2_obj: _EmbeddingOptionsProto
) -> 'EmbeddingOptions'

Creates a EmbeddingOptions object from the given protobuf object.

to_pb2

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to_pb2() -> _EmbeddingOptionsProto

Generates a protobuf object to pass to the C++ layer.

__eq__

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__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