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import random
import subprocess
import numpy as np
from scipy.io.wavfile import read
def weights_init(m):
classname = m.__class__.__name__
if classname.find("Conv") != -1:
m.weight.data.normal_(0.0, 0.02)
elif classname.find("BatchNorm2d") != -1:
m.weight.data.normal_(1.0, 0.02)
m.bias.data.fill_(0)
def get_commit_hash():
message = subprocess.check_output(["git", "rev-parse", "--short", "HEAD"])
return message.strip().decode('utf-8')
def read_wav_np(path):
sr, wav = read(path)
if len(wav.shape) == 2:
wav = wav[:, 0]
if wav.dtype == np.int16:
wav = wav / 32768.0
elif wav.dtype == np.int32:
wav = wav / 2147483648.0
elif wav.dtype == np.uint8:
wav = (wav - 128) / 128.0
wav = wav.astype(np.float32)
return sr, wav
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