kokeshing

import numpy as np
import librosa

"""
https://github.com/r9y9/wavenet_vocoder/blob/a835a8eebfec5e049d93f629c4ee2f1daab56329/train.py#L460
https://github.com/Rayhane-mamah/Tacotron-2/blob/ab5cb08a931fc842d3892ebeb27c8b8734ddd4b8/wavenet_vocoder/feeder.py#L368
https://github.com/kokeshing/WaveNet-Estimator/blob/cc2ee6bb699cf977356b23e7513ba549cdfc874f/dataset.py#L38
"""

kokeshing

import tensorflow as tf
import numpy as np

class CasualConv1D(tf.keras.layers.Wrapper):
    def __init__(self, filters, kernel_size=1, strides=1, data_format='channels_last',
                 dilation_rate=1, activation=None, use_bias=True, kernel_initializer=None,
                 bias_initializer=tf.zeros_initializer(), trainable=True, name=None, **kwargs
                 ):

        layer = tf.layers.Conv1D(

kokeshing

import tensorflow as tf
import numpy as np
import time


"""
    https://github.com/kweisamx/TensorFlow-ESPCN
"""
def PS_1(X, r, out_filters=1):
    Xc = tf.split(X, out_filters, 3)