code: def __call__(
      self,
      input_ids,
      attention_mask,
      position_ids,
      deterministic=True,
      init_cache: bool = False,
      output_attentions: bool = False,
      output_hidden_states: bool = False,
      return_dict: bool = True,
  ):
      input_embeds = self.wte(input_ids.astype("i4"))
  
      hidden_states = self.dropout(
          input_embeds, deterministic=deterministic
      )
  
      outputs = self.h(
          hidden_states,
          attention_mask,
          position_ids=position_ids,
          deterministic=deterministic,
          init_cache=init_cache,
          output_attentions=output_attentions,
          output_hidden_states=output_hidden_states,
          return_dict=return_dict,
      )
  
      hidden_states = outputs[0]
      hidden_states = self.ln_f(hidden_states)
  
      if output_hidden_states:
          all_hidden_states = outputs[1] + (hidden_states,)
          outputs = (hidden_states, all_hidden_states) + outputs[2:]
      else:
          outputs = (hidden_states,) + outputs[1:]
  
      if not return_dict:
          return tuple(v for v in outputs if v is not None)
  
      return FlaxBaseModelOutput(
          last_hidden_state=hidden_states,
          hidden_states=outputs[1],
          attentions=outputs[-1],
      )
  
imports: from functools import partial
  from typing import Optional, Tuple
  import numpy
  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 FlaxBaseModelOutput, FlaxCausalLMOutput
  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_gptj import GPTJConfig
label_desc: Use image node_id 2 for calling the FlaxGPTJModule obj's underlying member method code with example usage: obj.__call__(input_ids, attention_mask, position_ids, deterministic, init_cache, output_attentions, output_hidden_states, return_dict) and returns: FlaxBaseModelOutput, tuple