code: def __init__(
      self,
      parent,
      batch_size=13,
      seq_length=7,
      is_training=True,
      use_input_mask=True,
      vocab_size=99,
      hidden_size=32,
      num_hidden_layers=5,
      num_attention_heads=4,
      intermediate_size=37,
      hidden_act="gelu",
      hidden_dropout_prob=0.1,
      attention_probs_dropout_prob=0.1,
      max_position_embeddings=50,
      initializer_range=0.02,
      use_labels=True,
      scope=None,
  ):
      self.parent = parent
      self.batch_size = batch_size
      self.seq_length = seq_length
      self.is_training = is_training
      self.use_input_mask = use_input_mask
      self.vocab_size = vocab_size
      self.hidden_size = hidden_size
      self.num_hidden_layers = num_hidden_layers
      self.num_attention_heads = num_attention_heads
      self.intermediate_size = intermediate_size
      self.hidden_act = hidden_act
      self.hidden_dropout_prob = hidden_dropout_prob
      self.attention_probs_dropout_prob = attention_probs_dropout_prob
      self.max_position_embeddings = max_position_embeddings
      self.initializer_range = initializer_range
      self.use_labels = use_labels
      self.scope = scope
  
imports: import unittest
  from transformers import BertGenerationConfig, is_torch_available
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 1 to create a new BertGenerationEncoderTester object  with example: obj = BertGenerationEncoderTester(parent, batch_size, seq_length, is_training, use_input_mask, vocab_size, hidden_size, num_hidden_layers, num_attention_heads, intermediate_size, hidden_act, hidden_dropout_prob, attention_probs_dropout_prob, max_position_embeddings, initializer_range, use_labels, scope)