start new:
tmux
start new with session name:
tmux new -s myname
""" | |
"PyTorch must serve man, not rule over him" (c) DAO | |
A module for simple conversion between numpy and torch types. | |
Created out of frustration from lines like: | |
- x = Variable(torch.FloatTensor(x)).cuda() # now var(x, 'float32') | |
- (model(x).max(1)[1].data.cpu().numpy() == y).mean() # now numpy(x) | |
""" | |
import torch |
"""Simple example on how to log scalars and images to tensorboard without tensor ops. | |
License: BSD License 2.0 | |
""" | |
__author__ = "Michael Gygli" | |
import tensorflow as tf | |
from StringIO import StringIO | |
import matplotlib.pyplot as plt | |
import numpy as np |
import pandas as pd | |
def _map_to_pandas(rdds): | |
""" Needs to be here due to pickling issues """ | |
return [pd.DataFrame(list(rdds))] | |
def toPandas(df, n_partitions=None): | |
""" | |
Returns the contents of `df` as a local `pandas.DataFrame` in a speedy fashion. The DataFrame is | |
repartitioned if `n_partitions` is passed. |
#!/bin/bash | |
##################################################### | |
# Name: Bash CheatSheet for Mac OSX | |
# | |
# A little overlook of the Bash basics | |
# | |
# Usage: | |
# | |
# Author: J. Le Coupanec | |
# Date: 2014/11/04 |
toJson --- | |
Original Java object : ModelObject [name=myname, val=12, status=true, f=2.3] | |
Converted JSON string is : {"name":"myname","val":12,"status":true,"f":2.3} | |
fromJson---- | |
Original JSON string is : {"name":"myname","val":12,"status":true,"f":2.3} | |
Converted Java object : ModelObject [name=myname, val=12, status=true, f=2.3] |