code: def create_lightning_module(self) -> pl.LightningModule:
      return WaveNetLightningModule(
          lr=self.lr,
          weight_decay=self.weight_decay,
          model_kwargs=dict(
              bin_values=self.bin_centers,
              num_residual_channels=self.num_residual_channels,
              num_skip_channels=self.num_skip_channels,
              dilation_depth=self.dilation_depth,
              num_stacks=self.num_stacks,
              num_feat_dynamic_real=1
              + self.num_feat_dynamic_real
              + len(self.time_features),
              num_feat_static_real=max(1, self.num_feat_static_real),
              cardinality=self.cardinality,
              embedding_dimension=self.embedding_dimension,
              pred_length=self.prediction_length,
              num_parallel_samples=self.num_parallel_samples,
              temperature=self.temperature,
              use_log_scale_feature=self.use_log_scale_feature,
          ),
      )
  
imports: from typing import Any, Dict, List, Optional, Iterable
  import lightning.pytorch
  import torch
  import numpy
  from gluonts.core.component import validated
  from gluonts.dataset.common import Dataset
  from gluonts.dataset.field_names import FieldName
  from gluonts.dataset.loader import as_stacked_batches
  from gluonts.itertools import Cyclic
  from gluonts.torch.model.estimator import PyTorchLightningEstimator
  from gluonts.torch.model.predictor import PyTorchPredictor
  from gluonts.time_feature import get_seasonality, time_features_from_frequency_str, TimeFeature
  from gluonts.transform import Transformation, AddAgeFeature, AddObservedValuesIndicator, AddTimeFeatures, AsNumpyArray, Chain, ExpectedNumInstanceSampler, InstanceSampler, InstanceSplitter, SetField, RemoveFields, QuantizeMeanScaled, VstackFeatures, Identity, TestSplitSampler, ValidationSplitSampler
  from gluonts.maybe import unwrap_or
  from .module import WaveNet
  from .lightning_module import WaveNetLightningModule
label_desc: Use image node_id 6 for calling the WaveNetEstimator obj's underlying member method code with example usage: obj.create_lightning_module() and returns: WaveNetLightningModule