code: def __call__(self, inputs):
      inputs = jnp.asarray(inputs, self.dtype)
      kernel = self.param(
          "kernel", self.kernel_init, (inputs.shape[-1], self.features)
      )
      kernel = jnp.asarray(kernel, self.dtype)
      y = lax.dot_general(
          inputs,
          kernel,
          (((inputs.ndim - 1,), (0,)), ((), ())),
          precision=self.precision,
      )
      if self.use_bias:
          bias = self.param("bias", self.bias_init, (self.features,))
          bias = jnp.asarray(bias, self.dtype)
          y = y + bias
      return y
  
imports: import functools
  from pprint import pprint
  from typing import Any, Callable, Optional, Sequence
  from flax.core.frozen_dict import unfreeze
  from flax.linen import initializers
  from flax.linen import Module, compact, vmap
  from flax.linen.linear import PrecisionLike
  import jax
  from jax import lax, numpy, random
label_desc: Use image node_id 1 for calling the Dense obj's underlying member method code with example usage: obj.__call__(inputs) and returns: y