# Ptn LSTM
A long short-term memory  (LSTM) model consisting of one or more of a recurrent layer.  

    Args:
        input_size (int): The number of input features.  
        hidden_size (int): The number of output features of the hidden layer matrix.  
        num_layers (int): Number of hidden layers.  
        bias (bool): Use bias or not.  
        batch_first (bool): Indicates the shape of the input. Input is assumed to be a rank-3 tensor. If True, the shape is [Batch, Seq, Token]. If False, the shape is [Seq, Batch, Token]. Note that default is set to `True` unlike PyTorch's LSTM default model parameter.
        dropout (float): Dropout probability to be applied to the output of intermediate layers if non-zero. This will not be applied to the last layer's output.  
        bidirectional (bool): Processes the input in a backward direction and append the result to the output of the forward direction.  
        proj_size (int): If set to greater than 0, applies a projection to each output hidden state, reducing its dimensionality to proj_size.

## Input
| Name | Data type |
|---|---|
| input_size | Int |
| hidden_size | Int |
| num_layers | Int |
| bias | Boolean |
| batch_first | Boolean |
| dropout | Float |
| bidirectional | Boolean |
| proj_size | Int |

## Output
| Data type |
|---|
| Ptmodel |

<HR>
Category: PyTorch wrapper - Model

ComfyUI Pt Wrapper Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.