mirror of https://github.com/coqui-ai/TTS.git
54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
import numpy as np
|
|
|
|
|
|
def _pad_data(x, length):
|
|
_pad = 0
|
|
assert x.ndim == 1
|
|
return np.pad(x, (0, length - x.shape[0]), mode="constant", constant_values=_pad)
|
|
|
|
|
|
def prepare_data(inputs):
|
|
max_len = max((len(x) for x in inputs))
|
|
return np.stack([_pad_data(x, max_len) for x in inputs])
|
|
|
|
|
|
def _pad_tensor(x, length):
|
|
_pad = 0.0
|
|
assert x.ndim == 2
|
|
x = np.pad(x, [[0, 0], [0, length - x.shape[1]]], mode="constant", constant_values=_pad)
|
|
return x
|
|
|
|
|
|
def prepare_tensor(inputs, out_steps):
|
|
max_len = max((x.shape[1] for x in inputs))
|
|
remainder = max_len % out_steps
|
|
pad_len = max_len + (out_steps - remainder) if remainder > 0 else max_len
|
|
return np.stack([_pad_tensor(x, pad_len) for x in inputs])
|
|
|
|
|
|
def _pad_stop_target(x: np.ndarray, length: int, pad_val=1) -> np.ndarray:
|
|
"""Pad stop target array.
|
|
|
|
Args:
|
|
x (np.ndarray): Stop target array.
|
|
length (int): Length after padding.
|
|
pad_val (int, optional): Padding value. Defaults to 1.
|
|
|
|
Returns:
|
|
np.ndarray: Padded stop target array.
|
|
"""
|
|
assert x.ndim == 1
|
|
return np.pad(x, (0, length - x.shape[0]), mode="constant", constant_values=pad_val)
|
|
|
|
|
|
def prepare_stop_target(inputs, out_steps):
|
|
"""Pad row vectors with 1."""
|
|
max_len = max((x.shape[0] for x in inputs))
|
|
remainder = max_len % out_steps
|
|
pad_len = max_len + (out_steps - remainder) if remainder > 0 else max_len
|
|
return np.stack([_pad_stop_target(x, pad_len) for x in inputs])
|
|
|
|
|
|
def pad_per_step(inputs, pad_len):
|
|
return np.pad(inputs, [[0, 0], [0, 0], [0, pad_len]], mode="constant", constant_values=0.0)
|