Santiago Castro bryant1410

## layernorm_vs_fused.py
import time

import torch
import torch.nn as nn

from apex.normalization import FusedLayerNorm


torch.backends.cudnn.benchmark = True

## make-arXiv-package.sh
#!/usr/bin/env  bash

# This script is useful if:
#  - you have a manuscript that you want to upload to the arXiv,
#  - you are using biblatex, and
#  - you are using a recent version of texlive while arXiv is still on texlive2011
#
# Put this file in a directory containing the manuscript you want to
# upload to arXiv.org, and adapt the paths below.

## onehot_pandas_scikit.py
# -*- coding: utf-8 -*-
""" Small script that shows hot to do one hot encoding
    of categorical columns in a pandas DataFrame.

    See:
    http://scikit-learn.org/dev/modules/generated/sklearn.preprocessing.OneHotEncoder.html#sklearn.preprocessing.OneHotEncoder
    http://scikit-learn.org/dev/modules/generated/sklearn.feature_extraction.DictVectorizer.html
"""
import pandas
import random
	import time

	import torch
	import torch.nn as nn

	from apex.normalization import FusedLayerNorm


	torch.backends.cudnn.benchmark = True
	#!/usr/bin/env bash

	# This script is useful if:
	# - you have a manuscript that you want to upload to the arXiv,
	# - you are using biblatex, and
	# - you are using a recent version of texlive while arXiv is still on texlive2011
	#
	# Put this file in a directory containing the manuscript you want to
	# upload to arXiv.org, and adapt the paths below.
	# -- coding: utf-8 --
	""" Small script that shows hot to do one hot encoding
	of categorical columns in a pandas DataFrame.

	See:
	http://scikit-learn.org/dev/modules/generated/sklearn.preprocessing.OneHotEncoder.html#sklearn.preprocessing.OneHotEncoder
	http://scikit-learn.org/dev/modules/generated/sklearn.feature_extraction.DictVectorizer.html
	"""
	import pandas
	import random