move data.py and rename some files
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@ -132,7 +132,7 @@ dmypy.json
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.pyre/
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# Shell, vim, and output folder
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*.sh
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#*.sh
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*.swp
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runs
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syn_audios
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@ -13,10 +13,12 @@ from tensorboardX import SummaryWriter
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import paddle.fluid.dygraph as dg
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import paddle.fluid.layers as layers
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import paddle.fluid as fluid
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from parakeet.models.dataloader.ljspeech import LJSpeechLoader
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from parakeet.models.transformer_tts.transformerTTS import TransformerTTS
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from parakeet.models.transformer_tts.transformer_tts import TransformerTTS
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from parakeet.models.fastspeech.fastspeech import FastSpeech
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from parakeet.models.fastspeech.utils import get_alignment
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import sys
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sys.path.append("../transformer_tts")
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from data import LJSpeechLoader
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def load_checkpoint(step, model_path):
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model_dict, opti_dict = fluid.dygraph.load_dygraph(os.path.join(model_path, step))
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@ -1,4 +1,3 @@
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# train model
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# if you wish to resume from an exists model, uncomment --checkpoint_path and --fastspeech_step
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#CUDA_VISIBLE_DEVICES=0,1,2,3 \
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@ -14,7 +14,7 @@ from pprint import pprint
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from collections import OrderedDict
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from parakeet import audio
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from parakeet.models.transformer_tts.vocoder import Vocoder
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from parakeet.models.transformer_tts.transformerTTS import TransformerTTS
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from parakeet.models.transformer_tts.transformer_tts import TransformerTTS
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def load_checkpoint(step, model_path):
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model_dict, _ = fluid.dygraph.load_dygraph(os.path.join(model_path, step))
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@ -13,8 +13,8 @@ import paddle.fluid as fluid
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import paddle.fluid.dygraph as dg
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import paddle.fluid.layers as layers
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from parakeet.modules.utils import cross_entropy
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from parakeet.models.dataloader.ljspeech import LJSpeechLoader
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from parakeet.models.transformer_tts.transformerTTS import TransformerTTS
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from data import LJSpeechLoader
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from parakeet.models.transformer_tts.transformer_tts import TransformerTTS
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def load_checkpoint(step, model_path):
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model_dict, opti_dict = fluid.dygraph.load_dygraph(os.path.join(model_path, step))
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@ -10,7 +10,7 @@ from pprint import pprint
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import paddle.fluid as fluid
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import paddle.fluid.dygraph as dg
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import paddle.fluid.layers as layers
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from parakeet.models.dataloader.ljspeech import LJSpeechLoader
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from data import LJSpeechLoader
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from parakeet.models.transformer_tts.vocoder import Vocoder
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def load_checkpoint(step, model_path):
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@ -1,7 +1,7 @@
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import paddle.fluid.dygraph as dg
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import paddle.fluid as fluid
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from parakeet.modules.utils import *
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from parakeet.models.fastspeech.FFTBlock import FFTBlock
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from parakeet.models.fastspeech.fft_block import FFTBlock
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class Decoder(dg.Layer):
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def __init__(self,
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@ -1,7 +1,7 @@
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import paddle.fluid.dygraph as dg
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import paddle.fluid as fluid
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from parakeet.modules.utils import *
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from parakeet.models.fastspeech.FFTBlock import FFTBlock
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from parakeet.models.fastspeech.fft_block import FFTBlock
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class Encoder(dg.Layer):
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def __init__(self,
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@ -3,7 +3,7 @@ import paddle.fluid.dygraph as dg
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import paddle.fluid as fluid
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from parakeet.g2p.text.symbols import symbols
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from parakeet.models.transformer_tts.post_convnet import PostConvNet
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from parakeet.models.fastspeech.LengthRegulator import LengthRegulator
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from parakeet.models.fastspeech.length_regulator import LengthRegulator
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from parakeet.models.fastspeech.encoder import Encoder
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from parakeet.models.fastspeech.decoder import Decoder
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@ -11,16 +11,9 @@ class TransformerTTS(dg.Layer):
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self.config = config
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def forward(self, characters, mel_input, pos_text, pos_mel):
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# key (batch_size, seq_len, channel)
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# c_mask (batch_size, seq_len)
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# attns_enc (channel / 2, seq_len, seq_len)
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key, c_mask, attns_enc = self.encoder(characters, pos_text)
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# mel_output/postnet_output (batch_size, mel_len, n_mel)
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# attn_probs (128, mel_len, seq_len)
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# stop_preds (batch_size, mel_len, 1)
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# attns_dec (128, mel_len, mel_len)
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mel_output, postnet_output, attn_probs, stop_preds, attns_dec = self.decoder(key, key, mel_input, c_mask, pos_mel)
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return mel_output, postnet_output, attn_probs, stop_preds, attns_enc, attns_dec
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@ -2,7 +2,7 @@ import paddle.fluid.dygraph as dg
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import paddle.fluid as fluid
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from parakeet.modules.customized import Conv1D
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from parakeet.modules.utils import *
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from parakeet.models.transformer_tts.CBHG import CBHG
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from parakeet.models.transformer_tts.cbhg import CBHG
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class Vocoder(dg.Layer):
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"""
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