fix transformer_tts for function renaming of position_encoding
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@ -403,7 +403,7 @@ class TransformerTTS(nn.Layer):
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else:
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else:
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self.toned = False
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self.toned = False
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# position encoding matrix may be extended later
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# position encoding matrix may be extended later
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self.encoder_pe = pe.sinusoid_positional_encoding(1000, d_encoder)
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self.encoder_pe = pe.sinusoid_position_encoding(1000, d_encoder)
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self.encoder_pe_scalar = self.create_parameter(
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self.encoder_pe_scalar = self.create_parameter(
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[1], attr=I.Constant(1.))
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[1], attr=I.Constant(1.))
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self.encoder = TransformerEncoder(d_encoder, n_heads, d_ffn,
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self.encoder = TransformerEncoder(d_encoder, n_heads, d_ffn,
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@ -411,7 +411,7 @@ class TransformerTTS(nn.Layer):
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# decoder
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# decoder
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self.decoder_prenet = MLPPreNet(d_mel, d_prenet, d_decoder, dropout)
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self.decoder_prenet = MLPPreNet(d_mel, d_prenet, d_decoder, dropout)
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self.decoder_pe = pe.sinusoid_positional_encoding(1000, d_decoder)
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self.decoder_pe = pe.sinusoid_position_encoding(1000, d_decoder)
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self.decoder_pe_scalar = self.create_parameter(
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self.decoder_pe_scalar = self.create_parameter(
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[1], attr=I.Constant(1.))
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[1], attr=I.Constant(1.))
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self.decoder = TransformerDecoder(
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self.decoder = TransformerDecoder(
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@ -467,7 +467,8 @@ class TransformerTTS(nn.Layer):
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embed += self.tone_embed(tones)
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embed += self.tone_embed(tones)
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if embed.shape[1] > self.encoder_pe.shape[0]:
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if embed.shape[1] > self.encoder_pe.shape[0]:
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new_T = max(embed.shape[1], self.encoder_pe.shape[0] * 2)
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new_T = max(embed.shape[1], self.encoder_pe.shape[0] * 2)
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self.encoder_pe = pe.positional_encoding(0, new_T, self.d_encoder)
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self.encoder_pe = pe.sinusoid_position_encoding(new_T,
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self.d_encoder)
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pos_enc = self.encoder_pe[:T_enc, :] # (T, C)
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pos_enc = self.encoder_pe[:T_enc, :] # (T, C)
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x = embed.scale(math.sqrt(
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x = embed.scale(math.sqrt(
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self.d_encoder)) + pos_enc * self.encoder_pe_scalar
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self.d_encoder)) + pos_enc * self.encoder_pe_scalar
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@ -488,8 +489,8 @@ class TransformerTTS(nn.Layer):
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# twice its length if needed
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# twice its length if needed
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if x.shape[1] * self.r > self.decoder_pe.shape[0]:
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if x.shape[1] * self.r > self.decoder_pe.shape[0]:
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new_T = max(x.shape[1] * self.r, self.decoder_pe.shape[0] * 2)
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new_T = max(x.shape[1] * self.r, self.decoder_pe.shape[0] * 2)
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self.decoder_pe = pe.sinusoid_positional_encoding(new_T,
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self.decoder_pe = pe.sinusoid_position_encoding(new_T,
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self.d_decoder)
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self.d_decoder)
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pos_enc = self.decoder_pe[:T_dec * self.r:self.r, :]
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pos_enc = self.decoder_pe[:T_dec * self.r:self.r, :]
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x = x.scale(math.sqrt(
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x = x.scale(math.sqrt(
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self.d_decoder)) + pos_enc * self.decoder_pe_scalar
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self.d_decoder)) + pos_enc * self.decoder_pe_scalar
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