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cd ~/Desktop/nnmnkwii_gallery
python ./scripts/prepare_features.py ./data/NIT-ATR503/ --use_phone_alignment --question_path="./data/questions_jp.hed"

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import numpy as np
import os
from nnmnkwii.datasets import jsut

import librosa
import librosa.display
from matplotlib import pyplot as plt
from nnmnkwii.io import hts
from os.path import exists

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import numpy as np
import torch
import torch.nn.functional as F
import wavenet_vocoder
from nnmnkwii import preprocessing as P
from numpy import linspace, sin, pi, int16
from torch.autograd import Variable

sr = 4000

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FROM ubuntu:16.04

RUN apt-get update && apt-get install -y --no-install-recommends \
         build-essential \
         git \
         curl \
         ca-certificates \
         libjpeg-dev \
         libpng-dev && \
     rm -rf /var/lib/apt/lists/*

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import torch
from torch import nn
torch.manual_seed(1234)

model1 = nn.Sequential(*[nn.Linear(1, 1) for _ in range(2)])
layer = nn.Linear(1, 1)
model2 = nn.Sequential(*[layer for _ in range(2)])

print("Model1 (two different linear layers):")
assert not torch.equal(model1[0].weight, model1[1].weight)