HowToSD-ComfyUI-Pt-Wrapper/docs/reference/ptn_embedding_transformer_linear.md

Ptn Embedding Transformer Linear

A Transformer encoder model with a linear head.

Args:
    num_layers (int): Number of encoder layers in Transformer.
    vocabulary_size (int): The vocabulary size of the tokens.
    hidden_size (int): Hidden dimension (d_model) for each token of the Transformer.
    nhead (int): Number of attention heads.
    dim_feedforward (int): Feedforward dimension.
    dropout (float): Dropout rate for Transformer layers.
    nonlinearity (str): Activation function ('relu' or 'gelu') used in Transformer layers.
    layer_norm_eps (float): Epsilon value for layer normalization.
    batch_first (bool): Input shape format: True for (B, Seq, Feature), False for (Seq, B, Feature).
    norm_first (bool): Whether to apply normalization before attention/feedforward.
    bias (bool): Use bias in the Transformer layers.
    max_length (int): Maximum input sequence length (for positional embedding).
    linear_output_size (int): Output size of the final linear layer.
    linear_bias (bool): Use bias in the linear layer.

Input

Name	Data type
num_layers	Int
vocabulary_size	Int
hidden_size	Int
nhead	Int
dim_feedforward	Int
dropout	Float
nonlinearity
layer_norm_eps	Float
batch_first	Boolean
norm_first	Boolean
bias	Boolean
max_length	Int
linear_output_size	Int
linear_bias	Boolean

Output

Data type
Ptmodel

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Category: PyTorch wrapper - Model

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