allow_cache: true
batch_size: 1
config: ./ttsexamples/tacotron2/conf/tacotron2.v1.yaml
dev_dir: /content/dump_ljspeech/valid
end_ratio_value: 0.0
eval_interval_steps: 50
format: npy
gradient_accumulation_steps: 1
hop_size: 256
is_shuffle: true
log_interval_steps: 20
max_char_length: 128
max_mel_length: 257
mel_length_threshold: 32
mixed_precision: false
model_type: tacotron2
num_save_intermediate_results: 1
optimizer_params: {decay_steps: 150000, end_learning_rate: 1.0e-05, initial_learning_rate: 0.001,
  warmup_proportion: 0.02, weight_decay: 0.001}
outdir: ./ttsexamples/tacotron2/exp/train.tacotron2.v1/
pretrained: ''
remove_short_samples: true
resume: ''
save_interval_steps: 20
schedule_decay_steps: 50000
start_ratio_value: 0.5
start_schedule_teacher_forcing: 200001
tacotron2_params: {attention_dim: 128, attention_filters: 32, attention_kernel: 31,
  attention_type: lsa, dataset: ljspeech, decoder_lstm_units: 1024, embedding_dropout_prob: 0.1,
  embedding_hidden_size: 512, encoder_conv_activation: relu, encoder_conv_dropout_rate: 0.5,
  encoder_conv_filters: 512, encoder_conv_kernel_sizes: 5, encoder_lstm_units: 256,
  initializer_range: 0.02, n_conv_encoder: 5, n_conv_postnet: 5, n_lstm_decoder: 1,
  n_mels: 80, n_prenet_layers: 2, n_speakers: 1, postnet_conv_filters: 512, postnet_conv_kernel_sizes: 5,
  postnet_dropout_rate: 0.1, prenet_activation: relu, prenet_dropout_rate: 0.5, prenet_units: 256,
  reduction_factor: 1}
train_dir: /content/dump_ljspeech/train
train_max_steps: 200000
use_fal: false
use_fixed_shapes: true
use_norm: true
var_train_expr: null
verbose: 1
version: '0.0'