class_docstr: A simple base model that does not make use of a support set.
docstr: Computes the forecasts from the provided queries.
  
  Parameters
  ----------
  supps: Not used!
  query: The query.
docstr_tok: ["Computes","the","forecasts","from","the","provided","queries",".","Parameters","--","--","--","--","--","supps",":","Not","used","!","query",":","The","query","."]
code: def forward(
      self, supps: SeriesBatch, query: SeriesBatch
  ) -> torch.Tensor:
      """
      Computes the forecasts from the provided queries.
  
      Parameters
      ----------
      supps: Not used!
      query: The query.
      """
  
      x = self.feature_extractor(query)
      x = self.query_enc(query=x)
      x = self.decoder(query=x)
      return x
  
file_path: gluonts/src/gluonts/nursery/few_shot_prediction/src/meta/models/EcDc/series.py
imports: from typing import List
  import torch
  from lightkit.nn import Configurable
  from dataclasses import dataclass, field
  from meta.models.registry import register_model
  from meta.data.batch import SeriesBatch
  from meta.models.model import SeriesModel
  from .components import IdentityFeatureExtractor, LSTMQueryEncoder, FeedForwardQuantileDecoder
label_desc: Use image node_id 3 for calling the LSTMEncoderFeedforwardDecoder obj's underlying member method code with example usage: obj.forward(supps, query) and returns: x