# from fastai import *
# import librosa
# import soundfile as sf

#     fname = str(wav_file_path).split('/')[-1].split('.')[0]
#     print(wav_file_path)
#     print(fname)
#     wav, sr = librosa.load(wav_file_path,sr=None)
#     print(wav, sr)

#     #tfms 1: Noise addition:
#     wav_n = wav + 0.009*np.random.normal(0,1,len(wav))

#     #tfms 2: Shifting Sound wave:
#     wav_roll = np.roll(wav,int(sr/10))

#     #tfms 3: Time - stretching
#     factor = 0.4
#     wav_time_stch = librosa.effects.time_stretch(wav,factor)

#     #tfms 4: Pitch - Shifting
#     wav_pitch_sf = librosa.effects.pitch_shift(wav,sr,n_steps=-5)

#     wav_tfms = [wav_n,wav_roll,wav_time_stch,wav_pitch_sf]

#     sf.write(f'{tfms_folder_path}/{fname}_noise.wav', wav_n, sr)
#     sf.write(f'{tfms_folder_path}/{fname}_sshifting.wav', wav_roll, sr)
#     sf.write(f'{tfms_folder_path}/{fname}_stretch.wav', wav_time_stch, sr)
#     sf.write(f'{tfms_folder_path}/{fname}_pshift.wav', wav_pitch_sf, sr)

# data_path = pathlib.Path('./docs/wavefiledata/avicar_somedigits')
# !mkdir data_augs
# filenames = tf.io.gfile.glob(str(data_path)+"*/*.wav")
# for fpath in filenames:
#     audioDataTransforms(fpath, './data_augs')