Christian Hundt gravitino

## Dai said
 nvidia-smi dmon -s pucvmt -o T

## Cell1+2.ipynb

      
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## Cell8.ipynb

      
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## Cell7.ipynb

      
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## Cell6.ipynb

      
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## Cell5.ipynb

      
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## Cell3+4.ipynb

      
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## mf.py
import tensorflow as tf
import tqdm

def tfmf(D, k,
         params_dict={"iters":2**14, "p":2, "h":1E-2, "init":"kmeans"},
         regularizer_dict={"lambda_C":1E-3, "lambda_B":1E-3, "p":1}):

   m, n = D.shape[0], D.shape[1]

   D_con = tf.constant(D)

## oss.py
import numpy as np
import pylab as pl
#import seaborn as sns
from sklearn.datasets import make_blobs, make_circles

def rbf_kernel(X, beta=None, p=2):


    num_data, num_feat = X.shape
    kernel = np.zeros((num_data, num_data))

## cuda_if.cu
#include <iostream>

// error makro
#define CUERR {                                                              \
    cudaError_t err;                                                         \
    if ((err = cudaGetLastError()) != cudaSuccess) {                         \
       std::cout << "CUDA error: " << cudaGetErrorString(err) << " : "       \
                 << __FILE__ << ", line " << __LINE__ << std::endl;          \
       exit(1);                                                              \
    }                                                                        \
	import tensorflow as tf
	import tqdm

	def tfmf(D, k,
	params_dict={"iters":2**14, "p":2, "h":1E-2, "init":"kmeans"},
	regularizer_dict={"lambda_C":1E-3, "lambda_B":1E-3, "p":1}):

	m, n = D.shape[0], D.shape[1]

	D_con = tf.constant(D)
	import numpy as np
	import pylab as pl
	#import seaborn as sns
	from sklearn.datasets import make_blobs, make_circles

	def rbf_kernel(X, beta=None, p=2):


	num_data, num_feat = X.shape
	kernel = np.zeros((num_data, num_data))
	#include <iostream>

	// error makro
	#define CUERR { \
	cudaError_t err; \
	if ((err = cudaGetLastError()) != cudaSuccess) { \
	std::cout << "CUDA error: " << cudaGetErrorString(err) << " : " \
	<< __FILE__ << ", line " << __LINE__ << std::endl; \
	exit(1); \
	} \