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docstrings for taoctron models

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erogol 2021-01-06 13:12:33 +01:00
parent 5a45af48f1
commit f288e9a260
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39
TTS/tts/models/tacotron.py
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@ -8,6 +8,45 @@ from TTS.tts.models.tacotron_abstract import TacotronAbstract
class Tacotron(TacotronAbstract):
"""Tacotron as in https://arxiv.org/abs/1703.10135
It's an autoregressive encoder-attention-decoder-postnet architecture.
Args:
num_chars (int): number of input characters to define the size of embedding layer.
num_speakers (int): number of speakers in the dataset. >1 enables multi-speaker training and model learns speaker embeddings.
r (int): initial model reduction rate.
postnet_output_dim (int, optional): postnet output channels. Defaults to 80.
decoder_output_dim (int, optional): decoder output channels. Defaults to 80.
attn_type (str, optional): attention type. Check ```TTS.tts.layers.common_layers.init_attn```. Defaults to 'original'.
attn_win (bool, optional): enable/disable attention windowing.
It especially useful at inference to keep attention alignment diagonal. Defaults to False.
attn_norm (str, optional): Attention normalization method. "sigmoid" or "softmax". Defaults to "softmax".
prenet_type (str, optional): prenet type for the decoder. Defaults to "original".
prenet_dropout (bool, optional): prenet dropout rate. Defaults to True.
forward_attn (bool, optional): enable/disable forward attention.
It is only valid if ```attn_type``` is ```original```. Defaults to False.
trans_agent (bool, optional): enable/disable transition agent in forward attention. Defaults to False.
forward_attn_mask (bool, optional): enable/disable extra masking over forward attention. Defaults to False.
location_attn (bool, optional): enable/disable location sensitive attention.
It is only valid if ```attn_type``` is ```original```. Defaults to True.
attn_K (int, optional): Number of attention heads for GMM attention. Defaults to 5.
separate_stopnet (bool, optional): enable/disable separate stopnet training without only gradient
flow from stopnet to the rest of the model. Defaults to True.
bidirectional_decoder (bool, optional): enable/disable bidirectional decoding. Defaults to False.
double_decoder_consistency (bool, optional): enable/disable double decoder consistency. Defaults to False.
ddc_r (int, optional): reduction rate for the coarse decoder of double decoder consistency. Defaults to None.
encoder_in_features (int, optional): input channels for the encoder. Defaults to 512.
decoder_in_features (int, optional): input channels for the decoder. Defaults to 512.
speaker_embedding_dim (int, optional): external speaker conditioning vector channels. Defaults to None.
gst (bool, optional): enable/disable global style token learning. Defaults to False.
gst_embedding_dim (int, optional): size of channels for GST vectors. Defaults to 512.
gst_num_heads (int, optional): number of attention heads for GST. Defaults to 4.
gst_style_tokens (int, optional): number of GST tokens. Defaults to 10.
gst_use_speaker_embedding (bool, optional): enable/disable inputing speaker embedding to GST. Defaults to False.
memory_size (int, optional): size of the history queue fed to the prenet. Model feeds the last ```memory_size```
output frames to the prenet.
"""
def __init__(self,
num_chars,
num_speakers,

37
TTS/tts/models/tacotron2.py
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@ -7,6 +7,43 @@ from TTS.tts.models.tacotron_abstract import TacotronAbstract
# TODO: match function arguments with tacotron
class Tacotron2(TacotronAbstract):
"""Tacotron2 as in https://arxiv.org/abs/1712.05884
It's an autoregressive encoder-attention-decoder-postnet architecture.
Args:
num_chars (int): number of input characters to define the size of embedding layer.
num_speakers (int): number of speakers in the dataset. >1 enables multi-speaker training and model learns speaker embeddings.
r (int): initial model reduction rate.
postnet_output_dim (int, optional): postnet output channels. Defaults to 80.
decoder_output_dim (int, optional): decoder output channels. Defaults to 80.
attn_type (str, optional): attention type. Check ```TTS.tts.layers.common_layers.init_attn```. Defaults to 'original'.
attn_win (bool, optional): enable/disable attention windowing.
It especially useful at inference to keep attention alignment diagonal. Defaults to False.
attn_norm (str, optional): Attention normalization method. "sigmoid" or "softmax". Defaults to "softmax".
prenet_type (str, optional): prenet type for the decoder. Defaults to "original".
prenet_dropout (bool, optional): prenet dropout rate. Defaults to True.
forward_attn (bool, optional): enable/disable forward attention.
It is only valid if ```attn_type``` is ```original```. Defaults to False.
trans_agent (bool, optional): enable/disable transition agent in forward attention. Defaults to False.
forward_attn_mask (bool, optional): enable/disable extra masking over forward attention. Defaults to False.
location_attn (bool, optional): enable/disable location sensitive attention.
It is only valid if ```attn_type``` is ```original```. Defaults to True.
attn_K (int, optional): Number of attention heads for GMM attention. Defaults to 5.
separate_stopnet (bool, optional): enable/disable separate stopnet training without only gradient
flow from stopnet to the rest of the model. Defaults to True.
bidirectional_decoder (bool, optional): enable/disable bidirectional decoding. Defaults to False.
double_decoder_consistency (bool, optional): enable/disable double decoder consistency. Defaults to False.
ddc_r (int, optional): reduction rate for the coarse decoder of double decoder consistency. Defaults to None.
encoder_in_features (int, optional): input channels for the encoder. Defaults to 512.
decoder_in_features (int, optional): input channels for the decoder. Defaults to 512.
speaker_embedding_dim (int, optional): external speaker conditioning vector channels. Defaults to None.
gst (bool, optional): enable/disable global style token learning. Defaults to False.
gst_embedding_dim (int, optional): size of channels for GST vectors. Defaults to 512.
gst_num_heads (int, optional): number of attention heads for GST. Defaults to 4.
gst_style_tokens (int, optional): number of GST tokens. Defaults to 10.
gst_use_speaker_embedding (bool, optional): enable/disable inputing speaker embedding to GST. Defaults to False.
"""
def __init__(self,
num_chars,
num_speakers,