Kento Nozawa nzw0301

`fmatrix.py`

python3 から logging が標準ライブラリにあります。import 時に衝突するため、別名に変更する必要があります。

	"""
	Modification version of https://github.com/optuna/optuna/pull/2303 with nccl backend

	Optuna example that optimizes multi-layer perceptrons using PyTorch distributed.

	In this example, we optimize the validation accuracy of hand-written digit recognition using
	PyTorch distributed data parallel and MNIST. We optimize the neural network architecture as well
	as the optimizer configuration. As it is too time consuming to use the whole MNIST dataset, we
	here use a small subset of it.

	# CIFAR-100

	import numpy as np
	import torchvision.transforms as transforms
	from torch.utils.data import DataLoader
	from torchvision.datasets import CIFAR100


	train_transform = transforms.Compose(
	[

-# -*- coding: utf-8 -*-
-require 'twitter'
-consumer_key = ''
-consumer_secret = ''
-access_token = ''
-access_token_secret = ''
-client = Twitter::REST::Client.new do |config|