class_docstr: Base class for all models that make predictions based on a query only
class_docstr_tok: ["Base","class","for","all","models","that","make","predictions","based","on","a","query","only"]
docstr: Computes the forecasts from query past.
  
  Parameters
  ----------
  query
      The query to be forecasted.
  
  Returns
  -------
  torch.Tensor
      The forecasts for the entire prediction length with shape `[num_queries,
      prediction_length, *]`.
docstr_tok: ["Computes","the","forecasts","from","query","past",".","Parameters","--","--","--","--","--","query","The","query","to","be","forecasted",".","Returns","--","--","--","-","torch.Tensor","The","forecasts","for","the","entire","prediction","length","with","shape","`","[","num_queries",",","prediction_length",",","*","]","`","."]
code: def forward(self, query: SeriesBatch) -> torch.Tensor:
      """
      Computes the forecasts from query past.
  
      Parameters
      ----------
      query
          The query to be forecasted.
  
      Returns
      -------
      torch.Tensor
          The forecasts for the entire prediction length with shape `[num_queries,
          prediction_length, *]`.
      """
  
file_path: gluonts/src/gluonts/nursery/few_shot_prediction/src/meta/models/model.py
imports: from abc import ABC, abstractmethod
  import torch
  from torch import nn
  from meta.data.batch import SeriesBatch
label_desc: Use image node_id 1 for calling the SeriesModel obj's underlying member method code with example usage: obj.forward(query) without return types