code: def __init__(
      self,
      parent,
      batch_size=13,
      prediction_length=7,
      context_length=14,
      cardinality=19,
      embedding_dimension=5,
      num_time_features=4,
      is_training=True,
      hidden_size=16,
      num_hidden_layers=2,
      num_attention_heads=4,
      intermediate_size=4,
      hidden_act="gelu",
      hidden_dropout_prob=0.1,
      attention_probs_dropout_prob=0.1,
      lags_sequence=[1, 2, 3, 4, 5],
  ):
      self.parent = parent
      self.batch_size = batch_size
      self.prediction_length = prediction_length
      self.context_length = context_length
      self.cardinality = cardinality
      self.num_time_features = num_time_features
      self.lags_sequence = lags_sequence
      self.embedding_dimension = embedding_dimension
      self.is_training = is_training
      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.encoder_seq_length = context_length
      self.decoder_seq_length = prediction_length
  
imports: import inspect
  import tempfile
  import unittest
  from huggingface_hub import hf_hub_download
  from transformers import is_torch_available
  from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
label_desc: Use image node_id 1 to create a new TimeSeriesTransformerModelTester object  with example: obj = TimeSeriesTransformerModelTester(parent, batch_size, prediction_length, context_length, cardinality, embedding_dimension, num_time_features, is_training, hidden_size, num_hidden_layers, num_attention_heads, intermediate_size, hidden_act, hidden_dropout_prob, attention_probs_dropout_prob, lags_sequence)