ragulpr

ragulpr

import torch
@profile
def keep():
    x = torch.randn(10000,100)
    y = x+1
    z = y**2
    w = z**2
    return w
# keep()

ragulpr

ragulpr

import numpy as np 
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt

import torch
import torch.nn as nn
import torch.nn.functional as F

print('torch.__version__',torch.__version__)

ragulpr

#!/bin/bash
# Go to a git-repository and neatly export the commit log.
# assumes "_Z_Z_Z_" and "_Y_Y_" "_X_X_" as unused characters 
# (just some improbable string i wrote)
# Truncate subject line sanitized (%f) or not (%s) to 79 %<(79,trunc)%f
for repo in $(ls -d */) ; do
    echo $repo
    cd $repo

    inside_git_repo="$(git rev-parse --is-inside-work-tree 2>/dev/null)"

ragulpr

commit,author_name,time_sec,subject,files_changed,lines_inserted,lines_deleted

8a428cdd35,"ekelsen",1524782988,"Merge-pull-request-18846-from-yongtang-04252018-FloorDiv-int8                  ",,,
ce733dc348,"ekelsen",1524781964,"Merge-pull-request-18881-from-ManHyuk-fix_typo                                 ",,,
5cd6a8d1ed,"ekelsen",1524781835,"Merge-pull-request-18907-from-yongtang-18363-mpi                               ",,,
d0b961306a,"ekelsen",1524781628,"Merge-pull-request-18896-from-KikaTech-fix_lite_topk                           ",,,
1bf9ec7f85,"Yong Tang",1524775671,"Fix-cmake-build-issues-with-GPU-on-Linux-18775                                 ",4,17,1  
4bd6ac7ce0,"Martin Wicke",1524775556,"Merge-pull-request-17602-from-joeyearsley-patch-1                              ",,,
26b2814096,"Yong Tang",1524774078,"Fix-build-error-with-MPI-support                                               ",1,1,
3e51dbba08,"Yifei Feng",1524767245,"Merge-pull-request-18885-from-drpngx-branch_194337205                   

ragulpr

import keras
from keras.layers import *
from keras.models import Model
import theano as T
import tensorflow as tf
print('theano ver.',T.__version__) 
print('tensorflow ver.',tf.__version__) 
print('keras ver.',keras.__version__) 
np.set_printoptions(precision=4)
np.random.seed(1)

ragulpr

import keras
from keras.layers import *
from keras.models import Model
import theano as T
import tensorflow as tf
print('theano ver.',T.__version__) 
print('tensorflow ver.',tf.__version__) 
print('keras ver.',keras.__version__) 
np.set_printoptions(precision=4)
np.random.seed(1)

ragulpr

def load_challenge_data(df,start_at,truncate_at):
    seq_len = np.max([truncate_at,df[:,1].max().astype(int)+1])    
    n_vars = df.shape[1]-2 # Drop unit_number and time
    n_series = int(df[:,0].max())

    feature_data   = np.zeros([seq_len,n_series,n_vars])
    times_to_event = np.zeros([seq_len,n_series,1])
    seq_lengths    = np.zeros([n_series])
    mask           = np.ones([seq_len,n_series,1])