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2025-03-25 19:25:13 -07:00

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Ptn GRU Linear

A recurrent neural network (GRU) model with a linear head.

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 in GRU.
    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 GRU 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.
    linear_output_size (int): The number of output features of the linear layer.
    linar_bias (bool): Use bias or not in linear layer.

Input

Name Data type
input_size Int
hidden_size Int
num_layers Int
bias Boolean
batch_first Boolean
dropout Float
bidirectional Boolean
linear_output_size Int
linear_bias Boolean

Output

Data type
Ptmodel

Category: PyTorch wrapper - Model

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