class_docstr: A single one-directional LSTM layer.
  
  The difference between a layer and a cell is that the layer can process a
  sequence, while the cell only expects an instantaneous value.
class_docstr_tok: ["A","single","one-directional","LSTM","layer",".","The","difference","between","a","layer","and","a","cell","is","that","the","layer","can","process","a","sequence",",","while","the","cell","only","expects","an","instantaneous","value","."]
code: def __init__(
      self,
      input_dim: int,
      hidden_dim: int,
      bias: bool = True,
      device=None,
      dtype=None,
  ) -> None:
      factory_kwargs = {"device": device, "dtype": dtype}
      super().__init__()
      self.cell = LSTMCell(
          input_dim, hidden_dim, bias=bias, **factory_kwargs
      )
  
imports: import numbers
  from typing import Optional, Tuple
  import warnings
  import torch
  from torch import Tensor
label_desc: Use image node_id 1 to create a new _LSTMSingleLayer object from inherited base classes: torch.nn with example: obj = _LSTMSingleLayer(input_dim, hidden_dim, bias, device, dtype)