pub struct LstmDataV1<'data> {
    pub model: Cow<'data, str>,
    pub dic: ZeroMap<'data, str, i16>,
    pub mat1: LstmMatrix<'data>,
    pub mat2: LstmMatrix<'data>,
    pub mat3: LstmMatrix<'data>,
    pub mat4: LstmMatrix<'data>,
    pub mat5: LstmMatrix<'data>,
    pub mat6: LstmMatrix<'data>,
    pub mat7: LstmMatrix<'data>,
    pub mat8: LstmMatrix<'data>,
    pub mat9: LstmMatrix<'data>,
}
Expand description

The struct that stores a LSTM model.

Fields

model: Cow<'data, str>

Name of the model

dic: ZeroMap<'data, str, i16>

The grapheme cluster dictionary used to train the model

mat1: LstmMatrix<'data>

The matrix associateed with embedding layer

mat2: LstmMatrix<'data>

The matrices associated with forward LSTM layer (embedding to hunits, hunits to hunits, and bias respectively)

mat3: LstmMatrix<'data>

The matrices associated with forward LSTM layer (embedding to hunits, hunits to hunits, and bias respectively)

mat4: LstmMatrix<'data>

The matrices associated with forward LSTM layer (embedding to hunits, hunits to hunits, and bias respectively)

mat5: LstmMatrix<'data>

The matrices associated with backward LSTM layer (embedding to hunits, hunits to hunits, and bias respectively)

mat6: LstmMatrix<'data>

The matrices associated with backward LSTM layer (embedding to hunits, hunits to hunits, and bias respectively)

mat7: LstmMatrix<'data>

The matrices associated with backward LSTM layer (embedding to hunits, hunits to hunits, and bias respectively)

mat8: LstmMatrix<'data>

The matrices associated with output layer (weight and bias term respectiely)

mat9: LstmMatrix<'data>

The matrices associated with output layer (weight and bias term respectiely)

Trait Implementations

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