code: def prepare_blenderbot_inputs_dict(
      config,
      input_ids,
      decoder_input_ids=None,
      attention_mask=None,
      decoder_attention_mask=None,
      head_mask=None,
      decoder_head_mask=None,
      cross_attn_head_mask=None,
  ):
      if attention_mask is None:
          attention_mask = np.where(
              input_ids != config.pad_token_id, 1, 0
          )
      if decoder_attention_mask is None:
          decoder_attention_mask = np.where(
              decoder_input_ids != config.pad_token_id, 1, 0
          )
      if head_mask is None:
          head_mask = np.ones(
              (config.encoder_layers, config.encoder_attention_heads)
          )
      if decoder_head_mask is None:
          decoder_head_mask = np.ones(
              (config.decoder_layers, config.decoder_attention_heads)
          )
      if cross_attn_head_mask is None:
          cross_attn_head_mask = np.ones(
              (config.decoder_layers, config.decoder_attention_heads)
          )
      return {
          "input_ids": input_ids,
          "decoder_input_ids": decoder_input_ids,
          "attention_mask": attention_mask,
          "decoder_attention_mask": attention_mask,
      }
  
imports: import unittest
  import numpy
  import timeout_decorator
  from transformers import BlenderbotSmallConfig, is_flax_available
  from transformers.testing_utils import require_flax, slow
  from ...generation.test_flax_utils import FlaxGenerationTesterMixin
  from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_blenderbot_inputs_dict(config, input_ids, decoder_input_ids, attention_mask, decoder_attention_mask, head_mask, decoder_head_mask, cross_attn_head_mask) and returns: dict