class_docstr: Class implementing Prophet operator in PyTorch.
code: def __init__(
      self,
      logical_operator,
      k,
      m,
      deltas,
      floor,
      start,
      t_scale,
      y_scale,
      changepoints_t,
      device,
  ):
      super(Prophet, self).__init__(logical_operator)
      self.regression = True
      self.k = k
      self.m = m
      self.deltas = torch.nn.Parameter(
          torch.Tensor(deltas), requires_grad=False
      )
      self.floor = floor
      self.start = start
      self.t_scale = t_scale
      self.y_scale = y_scale
      self.changepoints_t = torch.nn.Parameter(
          torch.Tensor(changepoints_t), requires_grad=False
      )
  
file_path: hummingbird/hummingbird/ml/operator_converters/prophet.py
imports: import numpy
  import torch
  from datetime import datetime
  from onnxconverter_common.registration import register_converter
  from ._physical_operator import PhysicalOperator
  from .None import constants
label_desc: Use image node_id 1 to create a new Prophet object from inherited base classes: PhysicalOperator, torch.nn with example: obj = Prophet(logical_operator, k, m, deltas, floor, start, t_scale, y_scale, changepoints_t, device)