code: def __call__(
      self,
      hidden_states,
      attention_mask,
      deterministic: bool = True,
      init_cache: bool = False,
      output_attentions: bool = False,
      output_hidden_states: bool = False,
  ):
      # decoder layers
      all_hidden_states = () if output_hidden_states else None
      all_self_attns = () if output_attentions else None
  
      for decoder_layer in self.layers:
          if output_hidden_states:
              all_hidden_states += (hidden_states,)
  
          layer_outputs = decoder_layer(
              hidden_states,
              attention_mask=attention_mask,
              init_cache=init_cache,
              output_attentions=output_attentions,
              deterministic=deterministic,
          )
  
          hidden_states = layer_outputs[0]
          if output_attentions:
              all_self_attns += (layer_outputs[1],)
  
      outputs = [hidden_states, all_hidden_states, all_self_attns]
      return outputs
  
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 2 for calling the FlaxOPTDecoderLayerCollection obj's underlying member method code with example usage: obj.__call__(hidden_states, attention_mask, deterministic, init_cache, output_attentions, output_hidden_states) and returns: outputs