keras/src/layers/core/embedding.py/Embedding/__init__
class Embedding:    def __init__(
        self,
        input_dim,
        output_dim,
        embeddings_initializer="uniform",
        embeddings_regularizer=None,
        embeddings_constraint=None,
        mask_zero=False,
        weights=None,
        lora_rank=None,
        **kwargs,
    ):
        input_length = kwargs.pop("input_length", None)
        if input_length is not None:
            warnings.warn(
                "Argument `input_length` is deprecated. Just remove it."
            )
        super().__init__(**kwargs)
        self.input_dim = input_dim
        self.output_dim = output_dim
        self.embeddings_initializer = initializers.get(embeddings_initializer)
        self.embeddings_regularizer = regularizers.get(embeddings_regularizer)
        self.embeddings_constraint = constraints.get(embeddings_constraint)
        self.mask_zero = mask_zero
        self.supports_masking = mask_zero
        self.autocast = False
        self.lora_rank = lora_rank
        self.lora_enabled = False

        if weights is not None:
            self.build()
            if not (isinstance(weights, list) and len(weights) == 1):
                weights = [weights]
            self.set_weights(weights)