code: def __call__(self, inputs):
      inputs = jnp.asarray(inputs, self.dtype)
      kernel = self.param(
          "kernel",
          jax.nn.initializers.normal(stddev=0.02),
          (self.features, inputs.shape[-1]),
      )
      kernel = jnp.asarray(kernel.transpose(), self.dtype)
      y = lax.dot_general(
          inputs,
          kernel,
          (((inputs.ndim - 1,), (0,)), ((), ())),
          precision=self.precision,
      )
      if self.use_bias:
          bias = self.param(
              "bias", jax.nn.initializers.zeros, (self.features,)
          )
          bias = jnp.asarray(bias, self.dtype)
          y = y + bias
      return y
  
imports: from typing import Any, Optional, Tuple
  import flax.linen
  import jax
  import jax.numpy
  from flax.core.frozen_dict import FrozenDict, freeze, unfreeze
  from flax.linen import combine_masks, make_causal_mask
  from flax.linen.attention import dot_product_attention_weights
  from flax.traverse_util import flatten_dict, unflatten_dict
  from jax import lax
  from ...modeling_flax_outputs import FlaxBaseModelOutputWithPastAndCrossAttentions, FlaxCausalLMOutputWithCrossAttentions
  from ...modeling_flax_utils import ACT2FN, FlaxPreTrainedModel, append_call_sample_docstring
  from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging
  from .configuration_gpt2 import GPT2Config
label_desc: Use image node_id 1 for calling the FlaxConv1D obj's underlying member method code with example usage: obj.__call__(inputs) and returns: y