keras/src/layers/core/einsum_dense.py/EinsumDense/__init__
class EinsumDense:    def __init__(
        self,
        equation,
        output_shape,
        activation=None,
        bias_axes=None,
        kernel_initializer="glorot_uniform",
        bias_initializer="zeros",
        kernel_regularizer=None,
        bias_regularizer=None,
        kernel_constraint=None,
        bias_constraint=None,
        lora_rank=None,
        **kwargs,
    ):
        super().__init__(**kwargs)
        self.equation = equation
        if isinstance(output_shape, int):
            self.partial_output_shape = (output_shape,)
        else:
            self.partial_output_shape = tuple(output_shape)
        self.bias_axes = bias_axes
        self.activation = activations.get(activation)
        self.kernel_initializer = initializers.get(kernel_initializer)
        self.bias_initializer = initializers.get(bias_initializer)
        self.kernel_regularizer = regularizers.get(kernel_regularizer)
        self.bias_regularizer = regularizers.get(bias_regularizer)
        self.kernel_constraint = constraints.get(kernel_constraint)
        self.bias_constraint = constraints.get(bias_constraint)
        self.lora_rank = lora_rank
        self.lora_enabled = False