Source code for openspeech.models.transformer.configurations

# MIT License
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# Copyright (c) 2021 Soohwan Kim and Sangchun Ha and Soyoung Cho
#
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from dataclasses import dataclass, field

from openspeech.dataclass.configurations import OpenspeechDataclass


@dataclass
class TransformerConfigs(OpenspeechDataclass):
    r"""
    This is the configuration class to store the configuration of
    a :class:`~openspeech.models.Transformer`.

    It is used to initiated an `Transformer` model.

    Configuration objects inherit from :class: `~openspeech.dataclass.configs.OpenspeechDataclass`.

    Args:
        model_name (str): Model name (default: transformer)
        d_model (int): Dimension of model. (default: 512)
        d_ff (int): Dimenstion of feed forward network. (default: 2048)
        num_attention_heads (int): The number of attention heads. (default: 8)
        num_encoder_layers (int): The number of encoder layers. (default: 12)
        num_decoder_layers (int): The number of decoder layers. (default: 6)
        encoder_dropout_p (float): The dropout probability of encoder. (default: 0.3)
        decoder_dropout_p (float): The dropout probability of decoder. (default: 0.3)
        ffnet_style (str): Style of feed forward network. (ff, conv) (default: ff)
        max_length (int): Max decoding length. (default: 128)
        teacher_forcing_ratio (float): The ratio of teacher forcing. (default: 1.0)
        joint_ctc_attention (bool): Flag indication joint ctc attention or not (default: False)
        optimizer (str): Optimizer for training. (default: adam)
    """
    model_name: str = field(
        default="transformer", metadata={"help": "Model name"}
    )
    d_model: int = field(
        default=512, metadata={"help": "Dimension of model."}
    )
    d_ff: int = field(
        default=2048, metadata={"help": "Dimenstion of feed forward network."}
    )
    num_attention_heads: int = field(
        default=8, metadata={"help": "The number of attention heads."}
    )
    num_encoder_layers: int = field(
        default=12, metadata={"help": "The number of encoder layers."}
    )
    num_decoder_layers: int = field(
        default=6, metadata={"help": "The number of decoder layers."}
    )
    encoder_dropout_p: float = field(
        default=0.3, metadata={"help": "The dropout probability of encoder."}
    )
    decoder_dropout_p: float = field(
        default=0.3, metadata={"help": "The dropout probability of decoder."}
    )
    ffnet_style: str = field(
        default="ff", metadata={"help": "Style of feed forward network. (ff, conv)"}
    )
    max_length: int = field(
        default=128, metadata={"help": "Max decoding length."}
    )
    teacher_forcing_ratio: float = field(
        default=1.0, metadata={"help": "The ratio of teacher forcing."}
    )
    joint_ctc_attention: bool = field(
        default=False, metadata={"help": "Flag indication joint ctc attention or not"}
    )
    optimizer: str = field(
        default="adam", metadata={"help": "Optimizer for training."}
    )


@dataclass
class JointCTCTransformerConfigs(OpenspeechDataclass):
    r"""
    This is the configuration class to store the configuration of
    a :class:`~openspeech.models.JointCTCTransformer`.

    It is used to initiated an `JointCTCTransformer` model.

    Configuration objects inherit from :class: `~openspeech.dataclass.configs.OpenspeechDataclass`.

    Args:
        model_name (str): Model name (default: joint_ctc_transformer)
        extractor (str): The CNN feature extractor. (default: conv2d_subsample)
        d_model (int): Dimension of model. (default: 512)
        d_ff (int): Dimenstion of feed forward network. (default: 2048)
        num_attention_heads (int): The number of attention heads. (default: 8)
        num_encoder_layers (int): The number of encoder layers. (default: 12)
        num_decoder_layers (int): The number of decoder layers. (default: 6)
        encoder_dropout_p (float): The dropout probability of encoder. (default: 0.3)
        decoder_dropout_p (float): The dropout probability of decoder. (default: 0.3)
        ffnet_style (str): Style of feed forward network. (ff, conv) (default: ff)
        max_length (int): Max decoding length. (default: 128)
        teacher_forcing_ratio (float): The ratio of teacher forcing. (default: 1.0)
        joint_ctc_attention (bool): Flag indication joint ctc attention or not (default: True)
        optimizer (str): Optimizer for training. (default: adam)
    """
    model_name: str = field(
        default="joint_ctc_transformer", metadata={"help": "Model name"}
    )
    extractor: str = field(
        default="conv2d_subsample", metadata={"help": "The CNN feature extractor."}
    )
    d_model: int = field(
        default=512, metadata={"help": "Dimension of model."}
    )
    d_ff: int = field(
        default=2048, metadata={"help": "Dimenstion of feed forward network."}
    )
    num_attention_heads: int = field(
        default=8, metadata={"help": "The number of attention heads."}
    )
    num_encoder_layers: int = field(
        default=12, metadata={"help": "The number of encoder layers."}
    )
    num_decoder_layers: int = field(
        default=6, metadata={"help": "The number of decoder layers."}
    )
    encoder_dropout_p: float = field(
        default=0.3, metadata={"help": "The dropout probability of encoder."}
    )
    decoder_dropout_p: float = field(
        default=0.3, metadata={"help": "The dropout probability of decoder."}
    )
    ffnet_style: str = field(
        default="ff", metadata={"help": "Style of feed forward network. (ff, conv)"}
    )
    max_length: int = field(
        default=128, metadata={"help": "Max decoding length."}
    )
    teacher_forcing_ratio: float = field(
        default=1.0, metadata={"help": "The ratio of teacher forcing. "}
    )
    joint_ctc_attention: bool = field(
        default=True, metadata={"help": "Flag indication joint ctc attention or not"}
    )
    optimizer: str = field(
        default="adam", metadata={"help": "Optimizer for training."}
    )


@dataclass
class TransformerWithCTCConfigs(OpenspeechDataclass):
    r"""
    This is the configuration class to store the configuration of
    a :class:`~openspeech.models.TransformerWithCTC`.

    It is used to initiated an `TransformerWithCTC` model.

    Configuration objects inherit from :class: `~openspeech.dataclass.configs.OpenspeechDataclass`.

    Args:
        model_name (str): Model name (default: transformer_with_ctc)
        extractor (str): The CNN feature extractor. (default: vgg)
        d_model (int): Dimension of model. (default: 512)
        d_ff (int): Dimenstion of feed forward network. (default: 2048)
        num_attention_heads (int): The number of attention heads. (default: 8)
        num_encoder_layers (int): The number of encoder layers. (default: 12)
        encoder_dropout_p (float): The dropout probability of encoder. (default: 0.3)
        ffnet_style (str): Style of feed forward network. (ff, conv) (default: ff)
        optimizer (str): Optimizer for training. (default: adam)
    """
    model_name: str = field(
        default="transformer_with_ctc", metadata={"help": "Model name"}
    )
    d_model: int = field(
        default=512, metadata={"help": "Dimension of model."}
    )
    d_ff: int = field(
        default=2048, metadata={"help": "Dimenstion of feed forward network."}
    )
    num_attention_heads: int = field(
        default=8, metadata={"help": "The number of attention heads."}
    )
    num_encoder_layers: int = field(
        default=12, metadata={"help": "The number of encoder layers."}
    )
    encoder_dropout_p: float = field(
        default=0.3, metadata={"help": "The dropout probability of encoder."}
    )
    ffnet_style: str = field(
        default="ff", metadata={"help": "Style of feed forward network. (ff, conv)"}
    )
    optimizer: str = field(
        default="adam", metadata={"help": "Optimizer for training."}
    )


@dataclass
class VGGTransformerConfigs(OpenspeechDataclass):
    r"""
    This is the configuration class to store the configuration of
    a :class:`~openspeech.models.VGGTransformer`.

    It is used to initiated an `VGGTransformer` model.

    Configuration objects inherit from :class: `~openspeech.dataclass.configs.OpenspeechDataclass`.

    Args:
        model_name (str): Model name (default: vgg_transformer)
        extractor (str): The CNN feature extractor. (default: vgg)
        d_model (int): Dimension of model. (default: 512)
        d_ff (int): Dimenstion of feed forward network. (default: 2048)
        num_attention_heads (int): The number of attention heads. (default: 8)
        num_encoder_layers (int): The number of encoder layers. (default: 12)
        num_decoder_layers (int): The number of decoder layers. (default: 6)
        encoder_dropout_p (float): The dropout probability of encoder. (default: 0.3)
        decoder_dropout_p (float): The dropout probability of decoder. (default: 0.3)
        ffnet_style (str): Style of feed forward network. (ff, conv) (default: ff)
        max_length (int): Max decoding length. (default: 128)
        teacher_forcing_ratio (float): The ratio of teacher forcing. (default: 1.0)
        joint_ctc_attention (bool): Flag indication joint ctc attention or not (default: False)
        optimizer (str): Optimizer for training. (default: adam)
    """
    model_name: str = field(
        default="vgg_transformer", metadata={"help": "Model name"}
    )
    extractor: str = field(
        default="vgg", metadata={"help": "The CNN feature extractor."}
    )
    d_model: int = field(
        default=512, metadata={"help": "Dimension of model."}
    )
    d_ff: int = field(
        default=2048, metadata={"help": "Dimenstion of feed forward network."}
    )
    num_attention_heads: int = field(
        default=8, metadata={"help": "The number of attention heads."}
    )
    num_encoder_layers: int = field(
        default=12, metadata={"help": "The number of encoder layers."}
    )
    num_decoder_layers: int = field(
        default=6, metadata={"help": "The number of decoder layers."}
    )
    encoder_dropout_p: float = field(
        default=0.3, metadata={"help": "The dropout probability of encoder."}
    )
    decoder_dropout_p: float = field(
        default=0.3, metadata={"help": "The dropout probability of decoder."}
    )
    ffnet_style: str = field(
        default="ff", metadata={"help": "Style of feed forward network. (ff, conv)"}
    )
    max_length: int = field(
        default=128, metadata={"help": "Max decoding length."}
    )
    teacher_forcing_ratio: float = field(
        default=1.0, metadata={"help": "The ratio of teacher forcing. "}
    )
    joint_ctc_attention: bool = field(
        default=False, metadata={"help": "Flag indication joint ctc attention or not"}
    )
    optimizer: str = field(
        default="adam", metadata={"help": "Optimizer for training."}
    )