code: def __call__(
      self,
      input_ids,
      attention_mask,
      position_ids,
      output_attentions: bool = False,
      output_hidden_states: bool = False,
      return_dict: bool = True,
      deterministic: bool = True,
      init_cache=False,
  ):
      decoder_outputs = self.decoder(
          input_ids=input_ids,
          attention_mask=attention_mask,
          position_ids=position_ids,
          output_attentions=output_attentions,
          output_hidden_states=output_hidden_states,
          return_dict=return_dict,
          deterministic=deterministic,
          init_cache=init_cache,
      )
  
      if not return_dict:
          return decoder_outputs
  
      return FlaxBaseModelOutput(
          last_hidden_state=decoder_outputs.last_hidden_state,
          hidden_states=decoder_outputs.hidden_states,
          attentions=decoder_outputs.attentions,
      )
  
imports: from functools import partial
  from typing import 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 jax.random import PRNGKey
  from ...modeling_flax_outputs import FlaxBaseModelOutput, FlaxMaskedLMOutput
  from ...modeling_flax_utils import ACT2FN, FlaxPreTrainedModel, append_call_sample_docstring
  from ...utils import add_start_docstrings, logging
  from .configuration_opt import OPTConfig
label_desc: Use image node_id 3 for calling the FlaxOPTModule obj's underlying member method code with example usage: obj.__call__(input_ids, attention_mask, position_ids, output_attentions, output_hidden_states, return_dict, deterministic, init_cache) and returns: FlaxBaseModelOutput, decoder_outputs