code: def __init__(
      self,
      parent,
      batch_size=13,
      seq_length=7,
      is_training=True,
      use_input_lengths=True,
      use_token_type_ids=True,
      use_labels=True,
      gelu_activation=True,
      sinusoidal_embeddings=False,
      causal=False,
      asm=False,
      n_langs=2,
      vocab_size=99,
      n_special=0,
      hidden_size=32,
      num_hidden_layers=2,
      num_attention_heads=4,
      hidden_dropout_prob=0.1,
      attention_probs_dropout_prob=0.1,
      max_position_embeddings=512,
      type_sequence_label_size=2,
      initializer_range=0.02,
      num_labels=2,
      num_choices=4,
      summary_type="last",
      use_proj=True,
      scope=None,
      bos_token_id=0,
  ):
      self.parent = parent
      self.batch_size = batch_size
      self.seq_length = seq_length
      self.is_training = is_training
      self.use_input_lengths = use_input_lengths
      self.use_token_type_ids = use_token_type_ids
      self.use_labels = use_labels
      self.gelu_activation = gelu_activation
      self.sinusoidal_embeddings = sinusoidal_embeddings
      self.causal = causal
      self.asm = asm
      self.n_langs = n_langs
      self.vocab_size = vocab_size
      self.n_special = n_special
      self.hidden_size = hidden_size
      self.num_hidden_layers = num_hidden_layers
      self.num_attention_heads = num_attention_heads
      self.hidden_dropout_prob = hidden_dropout_prob
      self.attention_probs_dropout_prob = attention_probs_dropout_prob
      self.max_position_embeddings = max_position_embeddings
      self.type_sequence_label_size = type_sequence_label_size
      self.initializer_range = initializer_range
      self.num_labels = num_labels
      self.num_choices = num_choices
      self.summary_type = summary_type
      self.use_proj = use_proj
      self.scope = scope
      self.bos_token_id = bos_token_id
  
imports: import unittest
  from transformers import XLMConfig, is_torch_available
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 to create a new XLMModelTester object  with example: obj = XLMModelTester(parent, batch_size, seq_length, is_training, use_input_lengths, use_token_type_ids, use_labels, gelu_activation, sinusoidal_embeddings, causal, asm, n_langs, vocab_size, n_special, hidden_size, num_hidden_layers, num_attention_heads, hidden_dropout_prob, attention_probs_dropout_prob, max_position_embeddings, type_sequence_label_size, initializer_range, num_labels, num_choices, summary_type, use_proj, scope, bos_token_id)