tflite_support.task.processor.EmbeddingOptions

Options for embedding processor.

tflite_support.task.processor.EmbeddingOptions(
    l2_normalize: Optional[bool] = None, quantize: Optional[bool] = None
)

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.

l2_normalize None
quantize None