#@markdown ## **3** Setting model parameters
#@markdown ---
#@markdown #### Your desired model name
model_filename = 'ninon-43' #@param {type: "string"}

#@markdown #### Upload your transcription / text to tacotron/filelists and right click -> copy path
Training_file = "filelists/list.txt" #@param {type: "string"}
hparams.training_files = Training_file
hparams.validation_files = Training_file

# hparams to Tune
#hparams.use_mmi=True,          # not used in this notebook
#hparams.use_gaf=True,          # not used in this notebook
#hparams.max_gaf=0.5,           # not used in this notebook
#hparams.drop_frame_rate = 0.2  # not used in this notebook
hparams.p_attention_dropout=0.1
hparams.p_decoder_dropout=0.1

# Quality of Life
generate_mels = True
hparams.show_alignments = True
alignment_graph_height = 600
alignment_graph_width = 1000

#@markdown #### Your batch size, lower if you don't have enough ram.
#@markdown ###### If you have a Tesla T4, it is recommended to use only 14 as your batch size.
hparams.batch_size =  43#@param {type: "integer"}
hparams.load_mel_from_disk = True
hparams.ignore_layers = [] # Layers to reset (None by default, other than foreign languages this param can be ignored)

#@markdown #### Your learning rate options.
#@markdown ###### You can choose to auto-calculate a learning rate or manually set one. The default of the original notebook is 5e-5.
# Learning Rate             # https://www.desmos.com/calculator/ptgcz4vzsw / http://boards.4channel.org/mlp/thread/34778298#p34789030
hparams.decay_start = 15000         # wait till decay_start to start decaying learning rate
autocalculate_learning_rate = True #@param {type:"boolean"}

  #@markdown ###### Manual learning rate override. Ignore if autocalculating learning rate.
if autocalculate_learning_rate == True:
  hparams.A_ = 0.001*(hparams.batch_size/256)**0.5 # Start/Max Learning Rate
else:
  hparams.A_ = 1e-5#@param {type:"number"}

hparams.B_ = 8000                   # Decay Rate
hparams.C_ = 0                      # Shift learning rate equation by this value
hparams.min_learning_rate = 1e-5    # Min Learning Rate

#@markdown #### Your total epochs to train to. Not recommended to change.

##@markdown #### Amount of epochs before stopping, preferably a very high amount to not stop.
hparams.epochs =  900#@param {type: "integer"}

torch.backends.cudnn.enabled = hparams.cudnn_enabled
torch.backends.cudnn.benchmark = hparams.cudnn_benchmark

#@markdown #### Where to save your model when training.
output_directory = '/content/drive/My Drive/colab/outdir' #@param {type: "string"}
log_directory = '/content/tacotron2/logs' # Location to save Log files locally
log_directory2 = '/content/drive/My Drive/colab/logs' # Location to copy log files (done at the end of each epoch to cut down on I/O)
checkpoint_path = output_directory+(r'/')+model_filename

#@markdown ---