Wanderer2014

Here's a simple implementation of bilinear interpolation on tensors using PyTorch.

I wrote this up since I ended up learning a lot about options for interpolation in both the numpy and PyTorch ecosystems. More generally than just interpolation, too, it's also a nice case study in how PyTorch magically can put very numpy-like code on the GPU (and by the way, do autodiff for you too).

For interpolation in PyTorch, this open issue calls for more interpolation features. There is now a nn.functional.grid_sample() feature but at least at first this didn't look like what I needed (but we'll come back to this later).

In particular I wanted to take an image, W x H x C, and sample it many times at different random locations. Note also that this is different than upsampling which exhaustively samples and also doesn't give us fle

##VGG19 model for Keras

This is the Keras model of the 19-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

	# derived from http://scikit-learn.org/stable/auto_examples/applications/topics_extraction_with_nmf_lda.html
	# explanations are located there : https://www.linkedin.com/pulse/dissociating-training-predicting-latent-dirichlet-lucien-tardres

	from sklearn.feature_extraction.text import CountVectorizer
	from sklearn.decomposition import LatentDirichletAllocation
	import pickle

	# create a blank model
	lda = LatentDirichletAllocation()

	PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked
	1 0 3 Braund, Mr. Owen Harris male 22 1 0 A/5 21171 7.25 S
	2 1 1 Cumings, Mrs. John Bradley (Florence Briggs Thayer) female 38 1 0 PC 17599 71.2833 C85 C
	3 1 3 Heikkinen, Miss. Laina female 26 0 0 STON/O2. 3101282 7.925 S
	4 1 1 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35 1 0 113803 53.1 C123 S
	5 0 3 Allen, Mr. William Henry male 35 0 0 373450 8.05 S
	6 0 3 Moran, Mr. James male 0 0 330877 8.4583 Q
	7 0 1 McCarthy, Mr. Timothy J male 54 0 0 17463 51.8625 E46 S
	8 0 3 Palsson, Master. Gosta Leonard male 2 3 1 349909 21.075 S
	9 1 3 Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) female 27 0 2 347742 11.1333 S