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def | __init__ (self, mask_padding, n_mel_channels, n_symbols, symbols_embedding_dim, encoder_kernel_size, encoder_n_convolutions, encoder_embedding_dim, attention_rnn_dim, attention_dim, attention_location_n_filters, attention_location_kernel_size, n_frames_per_step, decoder_rnn_dim, prenet_dim, max_decoder_steps, gate_threshold, p_attention_dropout, p_decoder_dropout, postnet_embedding_dim, postnet_kernel_size, postnet_n_convolutions, decoder_no_early_stopping) |
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def | parse_batch (self, batch) |
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def | parse_output (self, outputs, output_lengths) |
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def | forward (self, inputs) |
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def | infer (self, inputs, input_lengths) |
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◆ __init__()
def model.Tacotron2.__init__ |
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self, |
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mask_padding, |
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n_mel_channels, |
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n_symbols, |
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symbols_embedding_dim, |
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encoder_kernel_size, |
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encoder_n_convolutions, |
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encoder_embedding_dim, |
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attention_rnn_dim, |
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attention_dim, |
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attention_location_n_filters, |
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attention_location_kernel_size, |
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n_frames_per_step, |
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decoder_rnn_dim, |
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prenet_dim, |
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max_decoder_steps, |
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gate_threshold, |
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p_attention_dropout, |
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p_decoder_dropout, |
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postnet_embedding_dim, |
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postnet_kernel_size, |
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postnet_n_convolutions, |
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decoder_no_early_stopping |
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◆ parse_batch()
def model.Tacotron2.parse_batch |
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self, |
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batch |
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◆ parse_output()
def model.Tacotron2.parse_output |
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self, |
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outputs, |
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output_lengths |
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◆ forward()
def model.Tacotron2.forward |
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self, |
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inputs |
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◆ infer()
def model.Tacotron2.infer |
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self, |
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inputs, |
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input_lengths |
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◆ mask_padding
model.Tacotron2.mask_padding |
◆ n_mel_channels
model.Tacotron2.n_mel_channels |
◆ n_frames_per_step
model.Tacotron2.n_frames_per_step |
◆ embedding
model.Tacotron2.embedding |
◆ encoder
◆ decoder
◆ postnet
The documentation for this class was generated from the following file:
- demo/Tacotron2/tacotron2/model.py