koreyou

""" Implementation of OKapi BM25 with sklearn's TfidfVectorizer
Distributed as CC-0 (https://creativecommons.org/publicdomain/zero/1.0/)
"""

import numpy as np
from sklearn.feature_extraction.text import TfidfVectorizer
from scipy import sparse


class BM25(object):

oscarknagg

import torch

def projected_gradient_descent(model, x, y, loss_fn, num_steps, step_size, step_norm, eps, eps_norm,
                               clamp=(0,1), y_target=None):
    """Performs the projected gradient descent attack on a batch of images."""
    x_adv = x.clone().detach().requires_grad_(True).to(x.device)
    targeted = y_target is not None
    num_channels = x.shape[1]

    for i in range(num_steps):

tgsmith61591

# -*- coding: utf-8 -*-
#
# Author: Taylor G Smith
#
# Recommender system ranking metrics derived from Spark source for use with
# Python-based recommender libraries (i.e., implicit, 
# http://github.com/benfred/implicit/). These metrics are derived from the
# original Spark Scala source code for recommender metrics.
# https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/evaluation/RankingMetrics.scala

itspig

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127.0.0.1 log.ad.xiaomi.com
127.0.0.1 api.ad.xiaomi.com
127.0.0.1 sdkconfig.ad.xiaomi.com
127.0.0.1 o2o.api.xiaomi.com
127.0.0.1 gallery.pandora.xiaomi.com
127.0.0.1 mishop.pandora.xiaomi.com
127.0.0.1 upgrade.mishop.pandora.xiaomi.com

rahulrajaram

I recently came across the need to spawn multiple threads, each of which needs to write to the same file. Since the file will experience contention from multiple resources, we need to guarantee thread-safety.

NOTE: The following examples work with Python 3.x. To execute the following programs using Python 2.7, please replace threading.get_ident() with thread.get_ident(). As a result, you would need to import thread and not threading.

1. (The following example will take a very long time). It will create 200 threads, each of which will wait until a global lock is available for acquisition.

# threading_lock.py
import threading