Masaki Kozuki crcrpar

crcrpar / vgg16layers_no_top.py

Last active August 31, 2017 09:08

a wrapper of chainer VGG16Layers w/o fully connected layers.

	from __future__ import print_function
	import collections
	import os

	import numpy as np

	import chainer
	import chainer.functions as F
	import chainer.links as L

crcrpar / vgg.py

Created September 14, 2017 02:23

[PyTorch] pre-trained VGG16 for perceptual loss. e.g. Style Transfer

	"""Modified VGG16 to compute perceptual loss.

	This class is mostly copied from pytorch/examples.
	See, fast_neural_style in https://github.com/pytorch/examples.
	"""
	import torch
	from torchvision import models


	class VGG_OUTPUT(object):

crcrpar / vgg_19_get_hidden_feature_pytorch.py

Created October 6, 2017 11:11

wrapper for pretrained vgg19 in pytorch. you can get any hidden feature.

	import torch
	import torch.nn as nn
	from torchvision.models import vgg19


	"""
	sequential (
	# block_1
	(0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
	(1): ReLU (inplace)

crcrpar / vgg19_chainer.py

Last active July 30, 2018 06:50

loader for pretrained, official VGG19

	from __future__ import print_function
	import collections
	import os

	import numpy
	try:
	from PIL import Image
	available = True
	except ImportError as e:
	available = False

crcrpar / instance_normalization.py

Last active September 11, 2019 05:25

Instance Normalization in Chainer on top of Batch Normalization

	import numpy

	import chainer
	from chainer import configuration
	from chainer import cuda
	from chainer import functions
	from chainer import initializers
	from chainer import link
	from chainer.utils import argument
	from chainer import variable

crcrpar / mnist_pytorch2caffe2.py

Last active January 28, 2018 14:39

an example: pytorch to caffe2

	from __future__ import print_function
	import argparse
	from datetime import datetime as dt

	import numpy as np

	import onnx_caffe2.backend

	import torch
	import torch.nn as nn

crcrpar / Dockerfile

Created January 28, 2018 14:50

dockerfile to try pytorch to caffe2

	FROM caffe2ai/caffe2:c2v0.8.1.cpu.min.ubuntu16.04
	LABEL maintainer="[email protected]"

	# caffe2 install with cpu support

	RUN apt-get update && apt-get install -y --no-install-recommends \
	libgflags-dev \
	libgtest-dev \
	libiomp-dev \
	libleveldb-dev \

crcrpar / Dockerfile

Created April 17, 2018 13:24

Dockerfile for fastai

	FROM nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04

	RUN apt-get update && apt-get install -y --no-install-recommends \
	build-essential \
	cmake \
	git \
	curl \
	vim \
	ca-certificates \
	libjpeg-dev \

crcrpar / weight_norm.py

Created September 20, 2018 14:50

	import chainer
	from chainer.backends import cuda
	import chainer.link_hooks
	from chainer.link_hooks import _ForwardPreprocessCallbackArgs
	from chainer import variable


	def _get_axis(ndim, axis):
	axes = [axis]
	for i in range(ndim):

crcrpar / sample_spectral_norm.py

Created April 3, 2019 08:57

	import torch.nn as nn
	from torch.nn.utils import spectral_norm


	if __name__ == '__main__':
	layer = nn.Conv2d(3, 15, 3, 1, 1)
	layer = spectral_norm(layer)

	torch.save(layer.state_dict(), 'tmp.pth')