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tflite_support.task.text.TextEmbedder

Class that performs dense feature vector extraction on text.

number_of_output_layers Gets the number of output layers of the model.
options

Methods

cosine_similarity

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Computes cosine similarity [1] between two feature vectors.

create_from_file

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Creates the TextEmbedder object from a TensorFlow Lite model.

Args
file_path Path to the model.

Returns
TextEmbedder object that's created from the model file.

Raises
ValueError If failed to create TextEmbedder object from the provided file such as invalid file.
RuntimeError If other types of error occurred.

create_from_options

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Creates the TextEmbedder object from text embedder options.

Args
options Options for the text embedder task.

Returns
TextEmbedder object that's created from options.

Raises
ValueError If failed to create TextEmbedder object from TextEmbedderOptions such as missing the model.
RuntimeError If other types of error occurred.

embed

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Performs actual feature vector extraction on the provided text.

Args
text the input text, used to extract the feature vectors.

Returns
embedding result.

Raises
ValueError If any of the input arguments is invalid.
RuntimeError If failed to calculate the embedding vector.

get_embedding_dimension

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Gets the dimensionality of the embedding output.

Args
output_index The output index of output layer.

Returns
Dimensionality of the embedding output by the output_index'th output layer. Returns -1 if output_index is out of bounds.