# -*- coding: utf-8 -*-
# import tensorflow as tf
from dataclasses import dataclass
from .text import symbols

@dataclass
class HParams(object):
    """docstring for HParams."""
    ################################
    # Experiment Parameters        #
    ################################
    epochs=500
    iters_per_checkpoint=1000
    seed=1234
    dynamic_loss_scaling=True
    fp16_run=False
    distributed_run=False
    dist_backend="nccl"
    dist_url="tcp://localhost:54321"
    cudnn_enabled=True
    cudnn_benchmark=False
    ignore_layers=["embedding.weight"]
    ################################
    # Data Parameters             #
    ################################
    load_mel_from_disk=False
    training_files="lists/tts_data_train_processed.txt"
    validation_files="filelists/tts_data_val_processed.txt"
    text_cleaners=["english_cleaners"]
    ################################
    # Audio Parameters             #
    ################################
    max_wav_value=32768.0
    sampling_rate=16000
    filter_length=1024
    hop_length=256
    win_length=1024
    n_mel_channels=80
    mel_fmin=0.0
    mel_fmax=8000.0
    ################################
    # Model Parameters             #
    ################################
    n_symbols=len(symbols)
    symbols_embedding_dim=512
    # Encoder parameters
    encoder_kernel_size=5
    encoder_n_convolutions=3
    encoder_embedding_dim=512
    # Decoder parameters
    n_frames_per_step=1  # currently only 1 is supported
    decoder_rnn_dim=1024
    prenet_dim=256
    max_decoder_steps=1000
    gate_threshold=0.5
    p_attention_dropout=0.1
    p_decoder_dropout=0.1
    # Attention parameters
    attention_rnn_dim=1024
    attention_dim=128
    # Location Layer parameters
    attention_location_n_filters=32
    attention_location_kernel_size=31
    # Mel-post processing network parameters
    postnet_embedding_dim=512
    postnet_kernel_size=5
    postnet_n_convolutions=5
    ################################
    # Optimization Hyperparameters #
    ################################
    use_saved_learning_rate=False
    learning_rate=1e-3
    weight_decay=1e-6
    grad_clip_thresh=1.0
    batch_size=4
    mask_padding=True  # set model's padded outputs to padded values