torchaudio.prototype.models.conformer_wav2vec2_base

torchaudio.prototype.models.conformer_wav2vec2_base(extractor_input_dim: int = 64, extractor_output_dim: int = 256, encoder_projection_dropout: float = 0.0) → Wav2Vec2Model

Build Conformer Wav2Vec2 Model with “small” architecture from Conformer-Based Slef-Supervised Learning for Non-Speech Audio Tasks [Srivastava et al., 2022]

Parameters:

• extractor_input_dim (int, optional) – Input dimension of feature extractor. (Default: 64)

• extractor_output_dim (int, optional) – Output dimension of feature extractor. (Default: 256)

• encoder_projection_dropout (float, optional) – Dropout probability applied after feature projection. (Default: 0.0)

Returns:

The resulting wav2vec2 model with a conformer encoder and base configuration.

Return type:

Wav2Vec2Model