class_docstr: Removes leading or trailing elements of a time series.
  
  Takes as input a three-dimensional tensor (`B`, `C`, `L`) where `B` is the
  batch size, `C` is the number of input channels, and `L` is the length of
  the input. Outputs a three-dimensional tensor (`B`, `C`, `L - s`) where `s`
  is the number of elements to remove.
  
  Args:
      chomp_size : Number of elements to remove.
      last : If True, removes the last elements in the time dimension,
          If False, removes the fist elements.
class_docstr_tok: ["Removes","leading","or","trailing","elements","of","a","time","series",".","Takes","as","input","a","three-dimensional","tensor","(","`","B","`",",","`","C","`",",","`","L","`",")","where","`","B","`","is","the","batch","size",",","`","C","`","is","the","number","of","input","channels",",","and","`","L","`","is","the","length","of","the","input",".","Outputs","a","three-dimensional","tensor","(","`","B","`",",","`","C","`",",","`","L","-","s","`",")","where","`","s","`","is","the","number","of","elements","to","remove",".","Args",":","chomp_size",":","Number","of","elements","to","remove",".","last",":","If","True",",","removes","the","last","elements","in","the","time","dimension",",","If","False",",","removes","the","fist","elements","."]
code: def __init__(self, chomp_size: int, last: bool = True):
      super().__init__()
      self.chomp_size = chomp_size
      self.last = last
  
file_path: gluonts/src/gluonts/nursery/spliced_binned_pareto/tcn.py
imports: import torch
label_desc: Use image node_id 1 to create a new Chomp1d object from inherited base classes: torch.nn with example: obj = Chomp1d(chomp_size, last)