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
__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
|