r9y9

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)

r9y9

r9y9

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/*

r9y9

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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r9y9

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

r9y9

r9y9

r9y9

r9y9

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