# MIT License
#
# Copyright (c) 2021 Soohwan Kim and Sangchun Ha and Soyoung Cho
#
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# SOFTWARE.
from dataclasses import dataclass, field
from openspeech.dataclass.configurations import OpenspeechDataclass
[docs]@dataclass
class DeepSpeech2Configs(OpenspeechDataclass):
r"""
This is the configuration class to store the configuration of
a :class:`~openspeech.models.DeepSpeech2`.
It is used to initiated an `DeepSpeech2` model.
Configuration objects inherit from :class: `~openspeech.dataclass.configs.OpenspeechDataclass`.
Args:
model_name (str): Model name (default: deepspeech2)
num_rnn_layers (int): The number of rnn layers. (default: 5)
rnn_hidden_dim (int): The hidden state dimension of rnn. (default: 1024)
dropout_p (float): The dropout probability of model. (default: 0.3)
bidirectional (bool): If True, becomes a bidirectional encoders (default: True)
rnn_type (str): Type of rnn cell (rnn, lstm, gru) (default: gru)
activation (str): Type of activation function (default: str)
optimizer (str): Optimizer for training. (default: adam)
"""
model_name: str = field(
default="deepspeech2", metadata={"help": "Model name"}
)
rnn_type: str = field(
default="gru", metadata={"help": "Type of rnn cell (rnn, lstm, gru)"}
)
num_rnn_layers: int = field(
default=5, metadata={"help": "The number of rnn layers"}
)
rnn_hidden_dim: int = field(
default=1024, metadata={"help": "Hidden state dimenstion of RNN."}
)
dropout_p: float = field(
default=0.3, metadata={"help": "The dropout probability of model."}
)
bidirectional: bool = field(
default=True, metadata={"help": "If True, becomes a bidirectional encoders"}
)
activation: str = field(
default="hardtanh", metadata={"help": "Type of activation function"}
)
optimizer: str = field(
default="adam", metadata={"help": "Optimizer for training."}
)