gravitino

 nvidia-smi dmon -s pucvmt -o T

gravitino

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gravitino

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)

gravitino

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))

gravitino

#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);                                                              \
    }                                                                        \